Optimization processor for electronic data multiple transaction request messages

ABSTRACT

A optimization processor in a data transaction processing system receives an electronic data multiple transaction request message including multiple electronic data transaction requests, and determines whether some of the electronic data transaction requests should be routed through or bypass transaction integrity modules designed to detect and mitigate undesirable object conditions. The optimization processor may also determine whether some of the electronic data transaction requests should be routed through or bypass transaction processing modules designed to match or attempt to match electronic data transaction requests. The optimization processor may, in one embodiment, rely upon previous decisions made by the modules. The optimization processor may also access data structures storing information about a current environment state to determine whether an electronic data transaction request should be routed through the time consuming transaction integrity and transaction processing modules.

BACKGROUND

Computing systems, such as data transaction processing systems, oftenprocess data objects which are associated with values derived from orotherwise submitted or provided by external sources. Incoming messagesrelated to the data objects may include requests for transactions whichare triggered by, or otherwise perform actions on, the data objects atspecified values. Whether or not the attempted actions are executed orperformed depend in part on the values submitted with the incomingmessages and/or the rules and processing routines programmed into a datatransaction processing system.

One example of an environment including data objects having specifiedvalues is an electronic trading system wherein the values may besubmitted by participants, e.g. traders. Electronic trading systemsinclude objects having values associated therewith. Object values maychange over time, and some changes to the value of an object may beundesirable or based on incomplete or inaccurate data. Some integritysystems prevent undesirable changes in values over time or undesirablegaps between reference and received or incoming values.

However, such integrity systems add additional processing overhead,increasing the overall processing times and overall latency of a datatransaction processing system. Modern data transaction processingsystems process thousands, hundreds of thousands, or even millions ofmessages or transaction requests per day. Routing each message ortransaction request through integrity systems can create a bottleneck,creating latency and adversely affecting processing speeds.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts a computer network system, according to some embodiments.

FIG. 2 depicts a general computer system, according to some embodiments.

FIG. 3A depicts a storage data structure, according to some embodiments.

FIG. 3B depicts an alternative storage data structure, according to someembodiments.

FIG. 3C depicts an order book data structure, according to someembodiments.

FIG. 4 depicts a match engine module, according to some embodiments.

FIG. 5A depicts an example electronic data multiple transaction requestmessage, according to some embodiments.

FIG. 5B depicts another example electronic data multiple transactionrequest message, according to some embodiments.

FIGS. 6A to 6F depict block diagrams of an exemplary implementation ofan optimization module, according to some embodiments.

FIG. 7 depicts a high-level flowchart illustrating a method forprocessing electronic data multiple transaction request messages by adata transaction processing system, according to some embodiments.

FIG. 8 depicts another high-level flowchart illustrating a method forprocessing electronic data multiple transaction request messages by adata transaction processing system, according to some embodiments.

FIGS. 9A and 9B depicts representations of the operation of transactionintegrity modules.

FIG. 10 depicts an illustrative graph of an example transactionintegrity module.

FIG. 11 depicts an example of an event detected according to an exampletransaction integrity modules.

DETAILED DESCRIPTION

The disclosed embodiments relate generally to a data communicationssystem/network, for use by a data transaction processing system, whichincludes an optimization processor for rapidly determining whether a neworder type, an electronic data multiple transaction request message,received by the data transaction processing system and related to dataobjects should be routed through, or instead bypass, transactionintegrity modules designed to detect and mitigate undesirable objectconditions, as well as whether the message contents should be routedthrough, or instead bypass, transaction processing modules. Transactionintegrity modules, as well as transaction processing modules, maysignificantly increase the processing times of an exchange computingsystem, thereby reducing the volume of, and/or slowing the rate atwhich, messages may be processed by the electronic trading system.

The optimization processor may, in one embodiment, operate in a statefulmanner, i.e., rely upon previous decisions made by the data transactionprocessing system. The optimization processor may also access datastructures storing information about a current environment state todetermine whether a new transaction request should be routed through thetransaction integrity modules, thereby incurring the additionalprocessing time thereof, or whether a transaction request matchespreviously received but unsatisfied transaction requests, therebyincurring the additional processing time of a transaction processormodule pipeline.

The disclosed embodiments thus may be coupled with, but operateindependently of, the transaction integrity modules and/or order bookobjects that, when utilized, typically may significantly increasetransaction processing times.

As noted above, the disclosed embodiments also relate generally to anelectronic data multiple transaction request message that comprisesmultiple electronic data transaction requests, as well as to theoptimization processor for the electronic data multiple transactionrequest message. In one embodiment, the multiple electronic datatransaction requests in an electronic data multiple transaction requestmessage are sorted by value for each type, so that the optimizationprocessor initially analyzes one of the electronic data transactionrequests from the electronic data multiple transaction request messageand optimizes processing of the other electronic data transactionrequests based on the initially analyzed electronic data transactionrequest.

The data transaction processing system, in one embodiment, alsominimizes the amount of processing, e.g., due to the format of theelectronic data multiple transaction request message and/or theoptimized processing of the electronic data multiple transaction requestmessage, performed on electronic data transaction requests in the sameelectronic data multiple transaction request message, thus reducing thecomputing load of a transaction integrity module and an order bookmodule or match engine module of the data transaction processing system.In one embodiment, the data transaction processing system sorts theelectronic data transaction requests as discussed herein in anelectronic data multiple transaction request message to enableoptimization of the electronic data multiple transaction request messageby the optimization processor.

The disclosed embodiments also improve upon the technical field ofnetworking by reducing the number of different messages transmitted tothe exchange computing system. The disclosed system is a specificimplementation and practical application of an optimization processorthat determines when to bypass certain processing heavy, time consumingsoftware modules.

As the number of orders and trades processed by an exchange computingsystem increases, electronic data transaction request messages used tosubmit orders and trades and transmitted to the exchange computingsystem can strain computer systems and networks that are used totransmit such messages. Moreover, the exchange computing system mayinclude match engines that process the electronic data transactionrequest messages serially. A sender may submit multiple different ordersat substantially the same time, but the sender's orders may not beprocessed together because other orders (from other senders) mayintervene between orders transmitted from the same sender. The disclosedembodiments may, in one embodiment, improve user convenience byatomically processing electronic data transaction requests that areassociated with the same electronic data multiple transaction requestmessage.

At least some of the problems solved by the disclosed encoding systemare specifically rooted in technology, e.g., electronic data transactionrequest messages that are transmitted to a data transaction processingsystem are each individually processed by modules, increasing aper-transaction request overhead, and are solved by means of a technicalsolution, e.g., grouping multiple electronic data transaction requestsin an electronic data multiple transaction request message and utilizingone electronic data transaction request to potentially bypass processingof the other electronic data transaction requests, improving processingresponse times and the overall performance of the exchange computingsystem.

Accordingly, the resulting problem is a problem arising in computersystems due to the high volume, e.g., millions of electronic datatransaction requests a day, received from multiple different submittersvia different communications channels and processed by an exchangecomputing system. In cases where a sender may intend to submit a largegroup of the electronic data transaction requests together, thedisclosed embodiments may optimize processing of a subset of theelectronic data transaction requests that are all associated with a samesender or are associated with a common source, and may include a samecommon electronic data multiple transaction request message identifier.

When the optimization processor can avoid routing a message through apipeline or route leading to a transaction integrity module, and/or to atransaction processing module, e.g., perform selective routing, theprocessing capacity, speed, and throughput of the exchange computingsystem may be increased, i.e., the processing capacity of the exchangecomputing system to process new transactions, while maintaining/ensuringtransaction integrity, is maximized. The exchange computing system isaccordingly improved and faster while still implementing the transactionintegrity module and transaction processing logic when necessary andavoiding the additional processing burden when not necessary.

The solutions disclosed herein are, in one embodiment, implemented asautomatic responses and actions by an exchange computing systemcomputer.

The disclosed embodiments may, in one embodiment, implement a dual-passprocess that enables users to specify that the electronic datatransaction requests in an electronic data multiple transaction requestmessage should be processed atomically as a group.

The disclosed embodiments may also increase user convenience by allowingusers to submit laddered electronic data transaction requests, asdiscussed herein.

The disclosed embodiments may be directed to an exchange computingsystem that includes multiple hardware matching processors that match,or attempt to match, electronic data transaction requests with otherelectronic data transaction requests counter (or contra) thereto.Incoming electronic data transaction request messages (each oneincluding one electronic data transaction request) or electronic datamultiple transaction request messages (each one including multipleelectronic data transaction requests) may be received from differentclient computers over a data communication network, and outputelectronic data transaction result messages may be transmitted to theclient computers and may be indicative of results of the attempts tomatch incoming electronic data transaction requests.

The disclosed embodiments may be implemented in a data transactionprocessing system that processes data items or objects. Customer or userdevices (e.g., client computers) may submit electronic data transactionrequest messages, e.g., inbound messages, to the data transactionprocessing system over a data communication network. The electronic datatransaction request messages may include, for example, transactionmatching parameters, such as instructions and/or values, for processingthe data transaction request messages within the data transactionprocessing system. The instructions may be to perform transactions,e.g., buy or sell a quantity of a product at a range of values definedequations. Products, e.g., financial instruments, or order booksrepresenting the state of an electronic marketplace for a product, maybe represented as data objects within the exchange computing system. Theinstructions may also be conditional, e.g., buy or sell a quantity of aproduct at a given value if a trade for the product is executed at someother reference value. The data transaction processing system mayinclude various specifically configured matching processors that match,e.g., automatically, electronic data transaction request messages forthe same one of the data items or objects. The specifically configuredmatching processors may match, or attempt to match, electronic datatransaction request messages based on multiple transaction matchingparameters from the different client computers. The specificallyconfigured matching processors may additionally generate informationindicative of a state of an environment (e.g., the state of the orderbook) based on the processing, and report this information to datarecipient computing systems via outbound messages published via one ormore data feeds.

For example, one exemplary environment where the disclosed embodimentsmay be desirable is in financial markets, and in particular, electronicfinancial exchanges, such as a futures exchange, such as the ChicagoMercantile Exchange Inc. (CME).

Exchange Computing System

A financial instrument trading system, such as a futures exchange, suchas the Chicago Mercantile Exchange Inc. (CME), provides a contractmarket where financial instruments, e.g., futures and options onfutures, are traded using electronic systems. “Futures” is a term usedto designate all contracts for the purchase or sale of financialinstruments or physical commodities for future delivery or cashsettlement on a commodity futures exchange. A futures contract is alegally binding agreement to buy or sell a commodity at a specifiedprice at a predetermined future time. An option contract is the right,but not the obligation, to sell or buy the underlying instrument (inthis case, a futures contract) at a specified price on or before acertain expiration date. An option contract offers an opportunity totake advantage of futures price moves without actually having a futuresposition. The commodity to be delivered in fulfillment of the contract,or alternatively the commodity for which the cash market price shalldetermine the final settlement price of the futures contract, is knownas the contract's underlying reference or “underlier.” The underlying orunderlier for an options contract is the corresponding futures contractthat is purchased or sold upon the exercise of the option.

The terms and conditions of each futures contract are standardized as tothe specification of the contract's underlying reference commodity, thequality of such commodity, quantity, delivery date, and means ofcontract settlement. Cash settlement is a method of settling a futurescontract whereby the parties effect final settlement when the contractexpires by paying/receiving the loss/gain related to the contract incash, rather than by effecting physical sale and purchase of theunderlying reference commodity at a price determined by the futurescontract, price. Options and futures may be based on more generalizedmarket indicators, such as stock indices, interest rates, futurescontracts and other derivatives.

An exchange may provide for a centralized “clearing house” through whichtrades made must be confirmed, matched, and settled each day untiloffset or delivered. The clearing house may be an adjunct to anexchange, and may be an operating division of an exchange, which isresponsible for settling trading accounts, clearing trades, collectingand maintaining performance bond funds, regulating delivery, andreporting trading data. One of the roles of the clearing house is tomitigate credit risk. Clearing is the procedure through which theclearing house becomes buyer to each seller of a futures contract, andseller to each buyer, also referred to as a novation, and assumesresponsibility for protecting buyers and sellers from financial loss dueto breach of contract, by assuring performance on each contract. Aclearing member is a firm qualified to clear trades through the clearinghouse.

An exchange computing system may operate under a central counterpartymodel, where the exchange acts as an intermediary between marketparticipants for the transaction of financial instruments. Inparticular, the exchange computing system novates itself into thetransactions between the market participants, i.e., splits a giventransaction between the parties into two separate transactions where theexchange computing system substitutes itself as the counterparty to eachof the parties for that part of the transaction, sometimes referred toas a novation. In this way, the exchange computing system acts as aguarantor and central counterparty and there is no need for the marketparticipants to disclose their identities to each other, or subjectthemselves to credit or other investigations by a potentialcounterparty. For example, the exchange computing system insulates onemarket participant from the default by another market participant.Market participants need only meet the requirements of the exchangecomputing system. Anonymity among the market participants encourages amore liquid market environment as there are lower barriers toparticipation. The exchange computing system can accordingly offerbenefits such as centralized and anonymous matching and clearing.

A match engine within a financial instrument trading system may comprisea transaction processing system that processes a high volume, e.g.,millions, of messages or orders in one day. The messages are typicallysubmitted from market participant computers. Exchange match enginesystems may be subject to variable messaging loads due to variablemarket messaging activity. Performance of a match engine depends to acertain extent on the magnitude of the messaging load and the workneeded to process that message at any given time. An exchange matchengine may process large numbers of messages during times of high volumemessaging activity. With limited processing capacity, high messagingvolumes may increase the response time or latency experienced by marketparticipants.

The disclosed embodiments recognize that electronic messages such asincoming messages from market participants, i.e., “outright” messages,e.g., trade order messages, etc., are sent from client devicesassociated with market participants, or their representatives, to anelectronic trading or market system. For example, a market participantmay submit an electronic message to the electronic trading system thatincludes an associated specific action to be undertaken by theelectronic trading system, such as entering a new trade order into themarket or modifying an existing order in the market. In one embodiment,if a participant wishes to modify a previously sent request, e.g., aprior order which has not yet been processed or traded, they may send arequest message comprising a request to modify the prior request.

Electronic Data Transaction Request Messages

As used herein, a financial message, or an electronic message, refersboth to messages communicated by market participants to an electronictrading or market system and vice versa. The messages may becommunicated using packeting or other techniques operable to communicateinformation between systems and system components. Some messages may beassociated with actions to be taken in the electronic trading or marketsystem. In particular, in one embodiment, upon receipt of a request, atoken is allocated and included in a TCP shallow acknowledgmenttransmission sent back to the participant acknowledging receipt of therequest. It should be appreciated that while this shallow acknowledgmentis, in some sense, a response to the request, it does not confirm theprocessing of an order included in the request. The participant, i.e.,their device, then sends back a TCP acknowledgment which acknowledgesreceipt of the shallow acknowledgment and token.

Financial messages communicated to the electronic trading system, alsoreferred to as “inbound” messages, may include associated actions thatcharacterize the messages, such as trader orders, order modifications,order cancellations and the like, as well as other message types.Inbound messages may be sent from market participants, or theirrepresentatives, e.g., trade order messages, etc., to an electronictrading or market system. For example, a market participant may submitan electronic message to the electronic trading system that includes anassociated specific action to be undertaken by the electronic tradingsystem, such as entering a new trade order into the market or modifyingan existing order in the market. In one exemplary embodiment, theincoming request itself, e.g., the inbound order entry, may be referredto as an iLink message. iLink is a bidirectional communications/messageprotocol/message format implemented by the Chicago Mercantile ExchangeInc.

Financial messages communicated from the electronic trading system,referred to as “outbound” messages, may include messages responsive toinbound messages, such as confirmation messages, or other messages suchas market update messages, quote messages, and the like. Outboundmessages may be disseminated via data feeds.

Financial messages may further be categorized as having or reflecting animpact on a market or electronic marketplace, also referred to as an“order book” or “book,” for a traded product, such as a prevailing pricetherefore, number of resting orders at various price levels andquantities thereof, etc., or not having or reflecting an impact on amarket or a subset or portion thereof. In one embodiment, an electronicorder book may be understood to be an electronic collection of theoutstanding or resting orders for a financial instrument.

For example, a request to place a trade may result in a responseindicative of the trade either being matched with, or being rested on anorder book to await, a suitable counter-order. This response may includea message directed solely to the trader who submitted the order toacknowledge receipt of the order and report whether it was matched, andthe extent thereto, or rested. The response may further include amessage to all market participants reporting a change in the order bookdue to the order. This response may take the form of a report of thespecific change to the order book, e.g., an order for quantity X atprice Y was added to the book (referred to, in one embodiment, as aMarket By Order message), or may simply report the result, e.g., pricelevel Y now has orders for a total quantity of Z (where Z is the sum ofthe previous resting quantity plus quantity X of the new order). In somecases, requests may elicit a non-impacting response, such as temporallyproximate to the receipt of the request, and then cause a separatemarket-impact reflecting response at a later time. For example, a stoporder, fill or kill order (FOK), also known as an immediate or cancelorder, or other conditional request may not have an immediate marketimpacting effect, if at all, until the requisite conditions are met.

An acknowledgement or confirmation of receipt, e.g., a non-marketimpacting communication, may be sent to the trader simply confirmingthat the order was received. Upon the conditions being met and a marketimpacting result thereof occurring, a market-impacting message may betransmitted as described herein both directly back to the submittingmarket participant and to all market participants (in a Market By Price“MBP” e.g., Aggregated By Value (“ABV”) book, or Market By Order “MBO”,e.g., Per Order (“PO”) book format). It should be appreciated thatadditional conditions may be specified, such as a time or price limit,which may cause the order to be dropped or otherwise canceled and thatsuch an event may result in another non-market-impacting communicationinstead. In some implementations, market impacting communications may becommunicated separately from non-market impacting communications, suchas via a separate communications channel or feed.

It should be further appreciated that various types of market data feedsmay be provided which reflect different markets or aspects thereof.Market participants may then, for example, subscribe to receive thosefeeds of interest to them. For example, data recipient computing systemsmay choose to receive one or more different feeds. As market impactingcommunications usually tend to be more important to market participantsthan non-impacting communications, this separation may reduce congestionand/or noise among those communications having or reflecting an impacton a market or portion thereof. Furthermore, a particular market datafeed may only communicate information related to the top buy/sell pricesfor a particular product, referred to as “top of book” feed, e.g., onlychanges to the top 10 price levels are communicated. Such limitationsmay be implemented to reduce consumption of bandwidth and messagegeneration resources. In this case, while a request message may beconsidered market-impacting if it affects a price level other than thetop buy/sell prices, it will not result in a message being sent to themarket participants.

Examples of the various types of market data feeds which may be providedby electronic trading systems, such as the CME, in order to providedifferent types or subsets of market information or to provide suchinformation in different formats include Market By Order or Per Order,Market Depth (also known as Market by Price or Aggregated By Value to adesignated depth of the book), e.g., CME offers a 10-deep market byprice feed, Top of Book (a single depth Market by Price feed), andcombinations thereof. There may also be all manner of specialized feedsin terms of the content, i.e., providing, for example, derived data,such as a calculated index.

Market data feeds may be characterized as providing a “view” or“overview” of a given market, an aggregation or a portion thereof orchanges thereto. For example, a market data feed, such as a Market ByPrice (“MBP”) feed, also known as an Aggregated By Value (“ABV”) feed,may convey, with each message, the entire/current state of a market, orportion thereof, for a particular product as a result of one or moremarket impacting events. For example, an MBP message may convey a totalquantity of resting buy/sell orders at a particular price level inresponse to a new order being placed at that price. An MBP message mayconvey a quantity of an instrument which was traded in response to anincoming order being matched with one or more resting orders. MBPmessages may only be generated for events affecting a portion of amarket, e.g., only the top 10 resting buy/sell orders and, thereby, onlyprovide a view of that portion. As used herein, a market impactingrequest may be said to impact the “view” of the market as presented viathe market data feed.

An MBP feed may utilize different message formats for conveyingdifferent types of market impacting events. For example, when a neworder is rested on the order book, an MBP message may reflect thecurrent state of the price level to which the order was added, e.g., thenew aggregate quantity and the new aggregate number of resting orders.As can be seen, such a message conveys no information about theindividual resting orders, including the newly rested order, themselvesto the market participants. Only the submitting market participant, whoreceives a separate private message acknowledging the event, knows thatit was their order that was added to the book. Similarly, when a tradeoccurs, an MBP message may be sent which conveys the price at which theinstrument was traded, the quantity traded and the number ofparticipating orders, but may convey no information as to whoseparticular orders contributed to the trade. MBP feeds may further batchreporting of multiple events, i.e., report the result of multiple marketimpacting events in a single message.

Alternatively, a market data feed, referred to as a Market By Order(“MBO”) feed also known as a Per Order (“PO”) feed, may convey datareflecting a change that occurred to the order book rather than theresult of that change, e.g., that order ABC for quantity X was added toprice level Y or that order ABC and order XYZ traded a quantity X at aprice Y. In this case, the MBO message identifies only the change thatoccurred so a market participant wishing to know the current state ofthe order book must maintain their own copy and apply the changereflected in the message to know the current state. As can be seen,MBO/PO messages may carry much more data than MBP/ABV messages becauseMBO/PO messages reflect information about each order, whereas MBP/ABVmessages contain information about orders affecting some predeterminedvalue levels. Furthermore, because specific orders, but not thesubmitting traders thereof, are identified, other market participantsmay be able to follow that order as it progresses through the market,e.g., as it is modified, canceled, traded, etc.

An ABV book data object may include information about multiple values.The ABV book data object may be arranged and structured so thatinformation about each value is aggregated together. Thus, for a givenvalue V, the ABV book data object may aggregate all the information byvalue, such as for example, the number of orders having a certainposition at value V, the quantity of total orders resting at value V,etc. Thus, the value field may be the key, or may be a unique field,within an ABV book data object. In one embodiment, the value for eachentry within the ABV book data object is different. In one embodiment,information in an ABV book data object is presented in a manner suchthat the value field is the most granular field of information.

A PO book data object may include information about multiple orders. ThePO book data object may be arranged and structured so that informationabout each order is represented. Thus, for a given order O, the PO bookdata object may provide all of the information for order O. Thus, theorder field may be the key, or may be a unique field, within a PO bookdata object. In one embodiment, the order ID for each entry within thePO book data object is different. In one embodiment, information in a PObook data object is presented in a manner such that the order field isthe most granular field of information.

Thus, the PO book data object may include data about unique orders,e.g., all unique resting orders for a product, and the ABV book dataobject may include data about unique values, e.g., up to a predeterminedlevel, e.g., top ten price or value levels, for a product.

It should be appreciated that the number, type and manner of market datafeeds provided by an electronic trading system are implementationdependent and may vary depending upon the types of products traded bythe electronic trading system, customer/trader preferences, bandwidthand data processing limitations, etc. and that all such feeds, nowavailable or later developed, are contemplated herein. MBP/ABV andMBO/PO feeds may refer to categories/variations of market data feeds,distinguished by whether they provide an indication of the current stateof a market resulting from a market impacting event (MBP) or anindication of the change in the current state of a market due to amarket impacting event (MBO).

Messages, whether MBO or MBP, generated responsive to market impactingevents which are caused by a single order, such as a new order, an ordercancellation, an order modification, etc., are fairly simple and compactand easily created and transmitted. However, messages, whether MBO orMBP, generated responsive to market impacting events which are caused bymore than one order, such as a trade, may require the transmission of asignificant amount of data to convey the requisite information to themarket participants. For trades involving a large number of orders,e.g., a buy order for a quantity of 5000 which matches 5000 sell orderseach for a quantity of 1, a significant amount of information may needto be sent, e.g., data indicative of each of the 5000 trades that haveparticipated in the market impacting event.

In one embodiment, an exchange computing system may generate multipleorder book objects, one for each type of view that is published orprovided. For example, the system may generate a PO book object and anABV book object. It should be appreciated that each book object, or viewfor a product or market, may be derived from the Per Order book object,which includes all the orders for a given financial product or market.

An inbound message may include an order that affects the PO book object,the ABV book object, or both. An outbound message may include data fromone or more of the structures within the exchange computing system,e.g., the PO book object queues or the ABV book object queues.

Furthermore, each participating trader needs to receive a notificationthat their particular order has traded. Continuing with the example,this may require sending 5001 individual trade notification messages, oreven 10,000+ messages where each contributing side (buy vs. sell) isseparately reported, in addition to the notification sent to all of themarket participants.

As detailed in U.S. Patent Publication No. 2015/0161727, the entirety ofwhich is incorporated by reference herein and relied upon, it may berecognized that trade notifications sent to all market participants mayinclude redundant information repeated for each participating trade anda structure of an MBP trade notification message may be provided whichresults in a more efficient communication of the occurrence of a trade.The message structure may include a header portion which indicates thetype of transaction which occurred, i.e., a trade, as well as othergeneral information about the event, an instrument portion whichcomprises data about each instrument which was traded as part of thetransaction, and an order portion which comprises data about eachparticipating order. In one embodiment, the header portion may include amessage type, Transaction Time, Match Event Indicator, and Number ofMarket Data Entries (“No. MD Entries”) fields. The instrument portionmay include a market data update action indicator (“MD Update Action”),an indication of the Market Data Entry Type (“MD Entry Type”), anidentifier of the instrument/security involved in the transaction(“Security ID”), a report sequence indicator (“Rpt Seq”), the price atwhich the instrument was traded (“MD Entry PX”), the aggregate quantitytraded at the indicated price (“ConsTradeQty”), the number ofparticipating orders (“NumberOfOrders”), and an identifier of theaggressor side (“Aggressor Side”) fields. The order portion may furtherinclude an identifier of the participating order (“Order ID”), describedin more detail below, and the quantity of the order traded (“MD EntrySize”) fields. It should be appreciated that the particular fieldsincluded in each portion are implementation dependent and that differentfields in addition to, or in lieu of, those listed may be includeddepending upon the implementation. It should be appreciated that theexemplary fields can be compliant with the FIX binary and/or FIX/FASTprotocol for the communication of the financial information.

The instrument portion contains a set of fields, e.g., seven fieldsaccounting for 23 bytes, which are repeated for each participatinginstrument. In complex trades, such as trades involving combinationorders or strategies, e.g., spreads, or implied trades, there may bemultiple instruments being exchanged among the parties. In oneembodiment, the order portion includes only one field, accounting for 4bytes, for each participating order which indicates the quantity of thatorder which was traded. As will be discussed below, the order portionmay further include an identifier of each order, accounting for anadditional 8 bytes, in addition to the quantity thereof traded. Asshould be appreciated, data which would have been repeated for eachparticipating order, is consolidated or otherwise summarized in theheader and instrument portions of the message thereby eliminatingredundant information and, overall, significantly reducing the size ofthe message.

While the disclosed embodiments will be discussed with respect to an MBPmarket data feed, it should be appreciated that the disclosedembodiments may also be applicable to an MBO market data feed.

Market Segment Gateway

In one embodiment, the disclosed system may include a Market SegmentGateway (“MSG”) that is the point of ingress/entry and/oregress/departure for all transactions, i.e., the network traffic/packetscontaining the data therefore, specific to a single market at which theorder of receipt of those transactions may be ascribed. An MSG or MarketSegment Gateway may be utilized for the purpose of deterministicoperation of the market. The electronic trading system may includemultiple markets, and because the electronic trading system includes oneMSG for each market/product implemented thereby, the electronic tradingsystem may include multiple MSGs. For more detail on deterministicoperation in a trading system, see U.S. Patent Publication No.2015/0127513 entitled “Transactionally Deterministic High SpeedFinancial Exchange Having Improved, Efficiency, Communication,Customization, Performance, Access, Trading Opportunities, CreditControls, And Fault Tolerance” and filed on Nov. 7, 2013 (“the '513Publication”), the entire disclosure of which is incorporated byreference herein and relied upon.

For example, a participant may send a request for a new transaction,e.g., a request for a new order, to the MSG. The MSG extracts or decodesthe request message and determines the characteristics of the requestmessage.

The MSG may include, or otherwise be coupled with, a buffer, cache,memory, database, content addressable memory, data store or other datastorage mechanism, or combinations thereof, which stores data indicativeof the characteristics of the request message. The request is passed tothe transaction processing system, e.g., the match engine.

An MSG or Market Segment Gateway may be utilized for the purpose ofdeterministic operation of the market. Transactions for a particularmarket may be ultimately received at the electronic trading system viaone or more points of entry, e.g., one or more communicationsinterfaces, at which the disclosed embodiments apply determinism, whichas described may be at the point where matching occurs, e.g., at eachmatch engine (where there may be multiple match engines, each for agiven product/market, or moved away from the point where matching occursand closer to the point where the electronic trading system firstbecomes “aware” of the incoming transaction, such as the point wheretransaction messages, e.g., orders, ingress the electronic tradingsystem. Generally, the terms “determinism” or “transactionaldeterminism” may refer to the processing, or the appearance thereof, oforders in accordance with defined business rules. Accordingly, as usedherein, the point of determinism may be the point at which theelectronic trading system ascribes an ordering to incomingtransactions/orders relative to other incoming transactions/orders suchthat the ordering may be factored into the subsequent processing, e.g.,matching, of those transactions/orders as will be described. For moredetail on deterministic operation in a trading system, see the '513Publication.

Electronic Trading

Electronic trading of financial instruments, such as futures contracts,is conducted by market participants sending orders, such as to buy orsell one or more futures contracts, in electronic form to the exchange.These electronically submitted orders to buy and sell are then matched,if possible, by the exchange, i.e., by the exchange's matching engine,to execute a trade. Outstanding (unmatched, wholly unsatisfied/unfilledor partially satisfied/filled) orders are maintained in one or more datastructures or databases referred to as “order books,” such orders beingreferred to as “resting,” and made visible, i.e., their availability fortrading is advertised, to the market participants through electronicnotifications/broadcasts, referred to as market data feeds. An orderbook is typically maintained for each product, e.g., instrument, tradedon the electronic trading system and generally defines or otherwiserepresents the state of the market for that product, i.e., the currentprices at which the market participants are willing buy or sell thatproduct. As such, as used herein, an order book for a product may alsobe referred to as a market for that product.

Upon receipt of an incoming order to trade in a particular financialinstrument, whether for a single-component financial instrument, e.g., asingle futures contract, or for a multiple-component financialinstrument, e.g., a combination contract such as a spread contract, amatch engine, as described herein, will attempt to identify a previouslyreceived but unsatisfied order counter thereto, i.e., for the oppositetransaction (buy or sell) in the same financial instrument at the sameor better price (but not necessarily for the same quantity unless, forexample, either order specifies a condition that it must be entirelyfilled or not at all).

Previously received but unsatisfied orders, i.e., orders which eitherdid not match with a counter order when they were received or theirquantity was only partially satisfied, referred to as a partial fill,are maintained by the electronic trading system in an order bookdatabase/data structure to await the subsequent arrival of matchingorders or the occurrence of other conditions which may cause the orderto be modified or otherwise removed from the order book.

If the match engine identifies one or more suitable previously receivedbut unsatisfied counter orders, they, and the incoming order, arematched to execute a trade there between to at least partially satisfythe quantities of one or both the incoming order or the identifiedorders. If there remains any residual unsatisfied quantity of theidentified one or more orders, those orders are left on the order bookwith their remaining quantity to await a subsequent suitable counterorder, i.e., to rest. If the match engine does not identify a suitablepreviously received but unsatisfied counter order, or the one or moreidentified suitable previously received but unsatisfied counter ordersare for a lesser quantity than the incoming order, the incoming order isplaced on the order book, referred to as “resting”, with original orremaining unsatisfied quantity, to await a subsequently receivedsuitable order counter thereto. The match engine then generates matchevent data reflecting the result of this matching process. Othercomponents of the electronic trading system, as will be described, thengenerate the respective order acknowledgment and market data messagesand transmit those messages to the market participants.

Matching, which is a function typically performed by the exchange, is aprocess, for a given order which specifies a desire to buy or sell aquantity of a particular instrument at a particular price, ofseeking/identifying one or more wholly or partially, with respect toquantity, satisfying counter orders thereto, e.g., a sell counter to anorder to buy, or vice versa, for the same instrument at the same, orsometimes better, price (but not necessarily the same quantity), whichare then paired for execution to complete a trade between the respectivemarket participants (via the exchange) and at least partially satisfythe desired quantity of one or both of the order and/or the counterorder, with any residual unsatisfied quantity left to await anothersuitable counter order, referred to as “resting.” A match event mayoccur, for example, when an aggressing order matches with a restingorder. In one embodiment, two orders match because one order includesinstructions for or specifies buying a quantity of a particularinstrument at a particular price, and the other order includesinstructions for or specifies selling a (different or same) quantity ofthe instrument at a same or better price. It should be appreciated thatperforming an instruction associated with a message may includeattempting to perform the instruction. Whether or not an exchangecomputing system is able to successfully perform an instruction maydepend on the state of the electronic marketplace.

While the disclosed embodiments will be described with respect to aproduct by product or market by market implementation, e.g. implementedfor each market/order book, it will be appreciated that the disclosedembodiments may be implemented so as to apply across markets formultiple products traded on one or more electronic trading systems, suchas by monitoring an aggregate, correlated or other derivation of therelevant indicative parameters as described herein.

While the disclosed embodiments may be discussed in relation to futuresand/or options on futures trading, it should be appreciated that thedisclosed embodiments may be applicable to any equity, fixed incomesecurity, currency, commodity, options or futures trading system ormarket now available or later developed. It may be appreciated that atrading environment, such as a futures exchange as described herein,implements one or more economic markets where rights and obligations maybe traded. As such, a trading environment may be characterized by a needto maintain market integrity, transparency, predictability,fair/equitable access and participant expectations with respect thereto.In addition, it may be appreciated that electronic trading systemsfurther impose additional expectations and demands by marketparticipants as to transaction processing speed, latency, capacity andresponse time, while creating additional complexities relating thereto.Accordingly, as will be described, the disclosed embodiments may furtherinclude functionality to ensure that the expectations of marketparticipants are met, e.g., that transactional integrity and predictablesystem responses are maintained.

Financial instrument trading systems allow traders to submit orders andreceive confirmations, market data, and other information electronicallyvia electronic messages exchanged using a network. Electronic tradingsystems ideally attempt to offer a more efficient, fair and balancedmarket where market prices reflect a true consensus of the value oftraded products among the market participants, where the intentional orunintentional influence of any one market participant is minimized ifnot eliminated, and where unfair or inequitable advantages with respectto information access are minimized if not eliminated.

Electronic marketplaces attempt to achieve these goals by usingelectronic messages to communicate actions and related data of theelectronic marketplace between market participants, clearing firms,clearing houses, and other parties. The messages can be received usingan electronic trading system, wherein an action or transactionassociated with the messages may be executed. For example, the messagemay contain information relating to an order to buy or sell a product ina particular electronic marketplace, and the action associated with themessage may indicate that the order is to be placed in the electronicmarketplace such that other orders which were previously placed maypotentially be matched to the order of the received message. Thus theelectronic marketplace may conduct market activities through electronicsystems.

Clearing House

The clearing house of an exchange clears, settles and guarantees matchedtransactions in contracts occurring through the facilities of theexchange. In addition, the clearing house establishes and monitorsfinancial requirements for clearing members and conveys certain clearingprivileges in conjunction with the relevant exchange markets.

The clearing house establishes clearing level performance bonds(margins) for all products of the exchange and establishes minimumperformance bond requirements for customers of such products. Aperformance bond, also referred to as a margin requirement, correspondswith the funds that must be deposited by a customer with his or herbroker, by a broker with a clearing member or by a clearing member withthe clearing house, for the purpose of insuring the broker or clearinghouse against loss on open futures or options contracts. This is not apart payment on a purchase. The performance bond helps to ensure thefinancial integrity of brokers, clearing members and the exchange as awhole. The performance bond refers to the minimum dollar depositrequired by the clearing house from clearing members in accordance withtheir positions. Maintenance, or maintenance margin, refers to a sum,usually smaller than the initial performance bond, which must remain ondeposit in the customer's account for any position at all times. Theinitial margin is the total amount of margin per contract required bythe broker when a futures position is opened. A drop in funds below thislevel requires a deposit back to the initial margin levels, i.e., aperformance bond call. If a customer's equity in any futures positiondrops to or under the maintenance level because of adverse price action,the broker must issue a performance bond/margin call to restore thecustomer's equity. A performance bond call, also referred to as a margincall, is a demand for additional funds to bring the customer's accountback up to the initial performance bond level whenever adverse pricemovements cause the account to go below the maintenance.

The exchange derives its financial stability in large part by removingdebt obligations among market participants as they occur. This isaccomplished by determining a settlement price at the close of themarket each day for each contract and marking all open positions to thatprice, referred to as “mark to market.” Every contract is debited orcredited based on that trading session's gains or losses. As prices movefor or against a position, funds flow into and out of the tradingaccount. In the case of the CME, each business day by 6:40 a.m. Chicagotime, based on the mark-to-the-market of all open positions to theprevious trading day's settlement price, the clearing house pays to orcollects cash from each clearing member. This cash flow, known assettlement variation, is performed by CME's settlement banks based oninstructions issued by the clearing house. All payments to andcollections from clearing members are made in “same-day” funds. Inaddition to the 6:40 a.m. settlement, a daily intra-day mark-to-themarket of all open positions, including trades executed during theovernight GLOBEX®, the CME's electronic trading systems, trading sessionand the current day's trades matched before 11:15 a.m., is performedusing current prices. The resulting cash payments are made intra-day forsame day value. In times of extreme price volatility, the clearing househas the authority to perform additional intra-day mark-to-the-marketcalculations on open positions and to call for immediate payment ofsettlement variation. CME's mark-to-the-market settlement system differsfrom the settlement systems implemented by many other financial markets,including the interbank, Treasury securities, over-the-counter foreignexchange and debt, options, and equities markets, where participantsregularly assume credit exposure to each other. In those markets, thefailure of one participant can have a ripple effect on the solvency ofthe other participants. Conversely, CME's mark-to-the-market system doesnot allow losses to accumulate over time or allow a market participantthe opportunity to defer losses associated with market positions.

While the disclosed embodiments may be described in reference to theCME, it should be appreciated that these embodiments are applicable toany exchange. Such other exchanges may include a clearing house that,like the CME clearing house, clears, settles and guarantees all matchedtransactions in contracts of the exchange occurring through itsfacilities. In addition, such clearing houses establish and monitorfinancial requirements for clearing members and convey certain clearingprivileges in conjunction with the relevant exchange markets.

The disclosed embodiments are also not limited to uses by a clearinghouse or exchange for purposes of enforcing a performance bond or marginrequirement. For example, a market participant may use the disclosedembodiments in a simulation or other analysis of a portfolio. In suchcases, the settlement price may be useful as an indication of a value atrisk and/or cash flow obligation rather than a performance bond. Thedisclosed embodiments may also be used by market participants or otherentities to forecast or predict the effects of a prospective position onthe margin requirement of the market participant.

Trading Environment

The embodiments may be described in terms of a distributed computingsystem. The particular examples identify a specific set of componentsuseful in a futures and options exchange. However, many of thecomponents and inventive features are readily adapted to otherelectronic trading environments. The specific examples described hereinmay teach specific protocols and/or interfaces, although it should beunderstood that the principles involved may be extended to, or appliedin, other protocols and interfaces.

It should be appreciated that the plurality of entities utilizing orinvolved with the disclosed embodiments, e.g., the market participants,may be referred to by other nomenclature reflecting the role that theparticular entity is performing with respect to the disclosedembodiments and that a given entity may perform more than one roledepending upon the implementation and the nature of the particulartransaction being undertaken, as well as the entity's contractual and/orlegal relationship with another market participant and/or the exchange.

An exemplary trading network environment for implementing tradingsystems and methods is shown in FIG. 1. An exchange computer system 100receives messages that include orders and transmits market data relatedto orders and trades to users, such as via wide area network 162 and/orlocal area network 160 and computer devices 150, 152, 154, 156 and 158,as described herein, coupled with the exchange computer system 100.

Herein, the phrase “coupled with” is defined to mean directly connectedto or indirectly connected through one or more intermediate components.Such intermediate components may include both hardware and softwarebased components. Further, to clarify the use in the pending claims andto hereby provide notice to the public, the phrases “at least one of<A>, <B>, . . . and <N>” or “at least one of <A>, <B>, <N>, orcombinations thereof” are defined by the Applicant in the broadestsense, superseding any other implied definitions herebefore orhereinafter unless expressly asserted by the Applicant to the contrary,to mean one or more elements selected from the group comprising A, B, .. . and N, that is to say, any combination of one or more of theelements A, B, . . . or N including any one element alone or incombination with one or more of the other elements which may alsoinclude, in combination, additional elements not listed.

The exchange computer system 100 may be implemented with one or moremainframe, desktop or other computers, such as the example computer 200described herein with respect to FIG. 2. A user database 102 may beprovided which includes information identifying traders and other usersof exchange computer system 100, such as account numbers or identifiers,user names and passwords. An account data module 104 may be providedwhich may process account information that may be used during trades.

A match engine module 106 may be included to match bid and offer pricesand may be implemented with software that executes one or morealgorithms for matching bids and offers. A trade database 108 may beincluded to store information identifying trades and descriptions oftrades. In particular, a trade database may store informationidentifying the time that a trade took place and the contract price. Anorder book module 110 may be included to compute or otherwise determinecurrent bid and offer prices, e.g., in a continuous auction market, oralso operate as an order accumulation buffer for a batch auction market.

A market data module 112 may be included to collect market data andprepare the data for transmission to users.

A risk management module 114 may be included to compute and determine auser's risk utilization in relation to the user's defined riskthresholds. The risk management module 114 may also be configured todetermine risk assessments or exposure levels in connection withpositions held by a market participant. The risk management module 114may be configured to administer, manage or maintain one or moremargining mechanisms implemented by the exchange computer system 100.Such administration, management or maintenance may include managing anumber of database records reflective of margin accounts of the marketparticipants. In some embodiments, the risk management module 114implements one or more aspects of the disclosed embodiments, including,for instance, principal component analysis (PCA) based margining, inconnection with interest rate swap (IRS) portfolios, as describedherein.

A message management module 116 may be included to, among other things,receive, and extract orders from, electronic data transaction requestmessages. The message management module 116 may define a point ofingress into the exchange computer system 100 where messages are orderedand considered to be received by the system. This may be considered apoint of determinism in the exchange computer system 100 that definesthe earliest point where the system can ascribe an order of receipt toarriving messages. The point of determinism may or may not be at or nearthe demarcation point between the exchange computer system 100 and apublic/internet network infrastructure. The message management module116 processes messages by interpreting the contents of a message basedon the message transmit protocol, such as the transmission controlprotocol (“TCP”), to provide the content of the message for furtherprocessing by the exchange computer system.

The message management module 116 may also be configured to detectcharacteristics of an order for a transaction to be undertaken in anelectronic marketplace. For example, the message management module 116may identify and extract order content such as a price, product, volume,and associated market participant for an order. The message managementmodule 116 may also identify and extract data indicating an action to beexecuted by the exchange computer system 100 with respect to theextracted order. For example, the message management module 116 maydetermine the transaction type of the transaction requested in a givenmessage. A message may include an instruction to perform a type oftransaction. The transaction type may be, in one embodiment, arequest/offer/order to either buy or sell a specified quantity or unitsof a financial instrument at a specified price or value. The messagemanagement module 116 may also identify and extract other orderinformation and other actions associated with the extracted order. Allextracted order characteristics, other information, and associatedactions extracted from a message for an order may be collectivelyconsidered an order as described and referenced herein.

Order or message characteristics may include, for example, the state ofthe system after a message is received, arrival time (e.g., the time amessage arrives at the MSG or Market Segment Gateway), message type(e.g., new, modify, cancel), and the number of matches generated by amessage. Order or message characteristics may also include marketparticipant side (e.g., buyer or seller) or time in force (e.g., a gooduntil end of day order that is good for the full trading day, a gooduntil canceled ordered that rests on the order book until matched, or afill or kill order that is canceled if not filled immediately, or a filland kill order (FOK) that is filled to the maximum amount possible, andany remaining or unfilled/unsatisfied quantity is not stored on thebooks or allowed to rest).

An order processing module 118 may be included to decompose delta-based,spread instrument, bulk and other types of composite orders forprocessing by the order book module 110 and/or the match engine module106. The order processing module 118 may also be used to implement oneor more procedures related to clearing an order. The order may becommunicated from the message management module 118 to the orderprocessing module 118. The order processing module 118 may be configuredto interpret the communicated order, and manage the ordercharacteristics, other information, and associated actions as they areprocessed through an order book module 110 and eventually transacted onan electronic market. For example, the order processing module 118 maystore the order characteristics and other content and execute theassociated actions. In an embodiment, the order processing module mayexecute an associated action of placing the order into an order book foran electronic trading system managed by the order book module 110. In anembodiment, placing an order into an order book and/or into anelectronic trading system may be considered a primary action for anorder. The order processing module 118 may be configured in variousarrangements, and may be configured as part of the order book module110, part of the message management module 118, or as an independentfunctioning module.

As an intermediary to electronic trading transactions, the exchangebears a certain amount of risk in each transaction that takes place. Tothat end, the clearing house implements risk management mechanisms toprotect the exchange. One or more of the modules of the exchangecomputer system 100 may be configured to determine settlement prices forconstituent contracts, such as deferred month contracts, of spreadinstruments, such as for example, settlement module 120. A settlementmodule 120 (or settlement processor or other payment processor) may beincluded to provide one or more functions related to settling orotherwise administering transactions cleared by the exchange. Settlementmodule 120 of the exchange computer system 100 may implement one or moresettlement price determination techniques. Settlement-related functionsneed not be limited to actions or events occurring at the end of acontract term. For instance, in some embodiments, settlement-relatedfunctions may include or involve daily or other mark to marketsettlements for margining purposes. In some cases, the settlement module120 may be configured to communicate with the trade database 108 (or thememory(ies) on which the trade database 108 is stored) and/or todetermine a payment amount based on a spot price, the price of thefutures contract or other financial instrument, or other price data, atvarious times. The determination may be made at one or more points intime during the term of the financial instrument in connection with amargining mechanism. For example, the settlement module 120 may be usedto determine a mark to market amount on a daily basis during the term ofthe financial instrument. Such determinations may also be made on asettlement date for the financial instrument for the purposes of finalsettlement.

In some embodiments, the settlement module 120 may be integrated to anydesired extent with one or more of the other modules or processors ofthe exchange computer system 100. For example, the settlement module 120and the risk management module 114 may be integrated to any desiredextent. In some cases, one or more margining procedures or other aspectsof the margining mechanism(s) may be implemented by the settlementmodule 120.

One or more of the above-described modules of the exchange computersystem 100 may be used to gather or obtain data to support thesettlement price determination, as well as a subsequent marginrequirement determination. For example, the order book module 110 and/orthe market data module 112 may be used to receive, access, or otherwiseobtain market data, such as bid-offer values of orders currently on theorder books. The trade database 108 may be used to receive, access, orotherwise obtain trade data indicative of the prices and volumes oftrades that were recently executed in a number of markets. In somecases, transaction data (and/or bid/ask data) may be gathered orobtained from open outcry pits and/or other sources and incorporatedinto the trade and market data from the electronic trading system(s).

It should be appreciated that concurrent processing limits may bedefined by or imposed separately or in combination on one or more of thetrading system components, including the user database 102, the accountdata module 104, the match engine module 106, the trade database 108,the order book module 110, the market data module 112, the riskmanagement module 114, the message management module 116, the orderprocessing module 118, the settlement module 120, or other component ofthe exchange computer system 100.

The disclosed mechanisms may be implemented at any logical and/orphysical point(s), or combinations thereof, at which the relevantinformation/data (e.g., message traffic and responses thereto) may bemonitored or flows or is otherwise accessible or measurable, includingone or more gateway devices, modems, the computers or terminals of oneor more market participants, e.g., client computers, etc.

One skilled in the art will appreciate that one or more modulesdescribed herein may be implemented using, among other things, atangible computer-readable medium comprising computer-executableinstructions (e.g., executable software code). Alternatively, modulesmay be implemented as software code, firmware code, specificallyconfigured hardware or processors, and/or a combination of theaforementioned. For example, the modules may be embodied as part of anexchange 100 for financial instruments. It should be appreciated thedisclosed embodiments may be implemented as a different or separatemodule of the exchange computer system 100, or a separate computersystem coupled with the exchange computer system 100 so as to haveaccess to margin account record, pricing, and/or other data. Asdescribed herein, the disclosed embodiments may be implemented as acentrally accessible system or as a distributed system, e.g., where someof the disclosed functions are performed by the computer systems of themarket participants.

The trading network environment shown in FIG. 1 includes exemplarycomputer devices 150, 152, 154, 156 and 158 which depict differentexemplary methods or media by which a computer device may be coupledwith the exchange computer system 100 or by which a user maycommunicate, e.g., send and receive, trade or other informationtherewith. It should be appreciated that the types of computer devicesdeployed by traders and the methods and media by which they communicatewith the exchange computer system 100 is implementation dependent andmay vary and that not all of the depicted computer devices and/ormeans/media of communication may be used and that other computer devicesand/or means/media of communications, now available or later developedmay be used. Each computer device, which may comprise a computer 200described in more detail with respect to FIG. 2, may include a centralprocessor, specifically configured or otherwise, that controls theoverall operation of the computer and a system bus that connects thecentral processor to one or more conventional components, such as anetwork card or modem. Each computer device may also include a varietyof interface units and drives for reading and writing data or files andcommunicating with other computer devices and with the exchange computersystem 100. Depending on the type of computer device, a user caninteract with the computer with a keyboard, pointing device, microphone,pen device or other input device now available or later developed.

An exemplary computer device 150 is shown directly connected to exchangecomputer system 100, such as via a T1 line, a common local area network(LAN) or other wired and/or wireless medium for connecting computerdevices, such as the network 220 shown in FIG. 2 and described withrespect thereto. The exemplary computer device 150 is further shownconnected to a radio 168. The user of radio 168, which may include acellular telephone, smart phone, or other wireless proprietary and/ornon-proprietary device, may be a trader or exchange employee. The radiouser may transmit orders or other information to the exemplary computerdevice 150 or a user thereof. The user of the exemplary computer device150, or the exemplary computer device 150 alone and/or autonomously, maythen transmit the trade or other information to the exchange computersystem 100.

Exemplary computer devices 152 and 154 are coupled with a local areanetwork (“LAN”) 160 which may be configured in one or more of thewell-known LAN topologies, e.g., star, daisy chain, etc., and may use avariety of different protocols, such as Ethernet, TCP/IP, etc. Theexemplary computer devices 152 and 154 may communicate with each otherand with other computer and other devices which are coupled with the LAN160. Computer and other devices may be coupled with the LAN 160 viatwisted pair wires, coaxial cable, fiber optics or other wired orwireless media. As shown in FIG. 1, an exemplary wireless personaldigital assistant device (“PDA”) 158, such as a mobile telephone, tabletbased compute device, or other wireless device, may communicate with theLAN 160 and/or the Internet 162 via radio waves, such as via WiFi,Bluetooth and/or a cellular telephone based data communicationsprotocol. PDA 158 may also communicate with exchange computer system 100via a conventional wireless hub 164.

FIG. 1 also shows the LAN 160 coupled with a wide area network (“WAN”)162 which may be comprised of one or more public or private wired orwireless networks. In one embodiment, the WAN 162 includes the Internet162. The LAN 160 may include a router to connect LAN 160 to the Internet162. Exemplary computer device 156 is shown coupled directly to theInternet 162, such as via a modem, DSL line, satellite dish or any otherdevice for connecting a computer device to the Internet 162 via aservice provider therefore as is known. LAN 160 and/or WAN 162 may bethe same as the network 220 shown in FIG. 2 and described with respectthereto.

Users of the exchange computer system 100 may include one or more marketmakers 166 which may maintain a market by providing constant bid andoffer prices for a derivative or security to the exchange computersystem 100, such as via one of the exemplary computer devices depicted.The exchange computer system 100 may also exchange information withother match or trade engines, such as trade engine 170. One skilled inthe art will appreciate that numerous additional computers and systemsmay be coupled to exchange computer system 100. Such computers andsystems may include clearing, regulatory and fee systems.

The operations of computer devices and systems shown in FIG. 1 may becontrolled by computer-executable instructions stored on anon-transitory computer-readable medium. For example, the exemplarycomputer device 152 may store computer-executable instructions forreceiving order information from a user, transmitting that orderinformation to exchange computer system 100 in electronic messages,extracting the order information from the electronic messages, executingactions relating to the messages, and/or calculating values fromcharacteristics of the extracted order to facilitate matching orders andexecuting trades. In another example, the exemplary computer device 154may include computer-executable instructions for receiving market datafrom exchange computer system 100 and displaying that information to auser.

Numerous additional servers, computers, handheld devices, personaldigital assistants, telephones and other devices may also be connectedto exchange computer system 100. Moreover, one skilled in the art willappreciate that the topology shown in FIG. 1 is merely an example andthat the components shown in FIG. 1 may include other components notshown and be connected by numerous alternative topologies.

Referring now to FIG. 2, an illustrative embodiment of a generalcomputer system 200 is shown. The computer system 200 can include a setof instructions that can be executed to cause the computer system 200 toperform any one or more of the methods or computer based functionsdisclosed herein. The computer system 200 may operate as a standalonedevice or may be connected, e.g., using a network, to other computersystems or peripheral devices. Any of the components discussed herein,such as processor 202, may be a computer system 200 or a component inthe computer system 200. The computer system 200 may be specificallyconfigured to implement a match engine, margin processing, payment orclearing function on behalf of an exchange, such as the ChicagoMercantile Exchange, of which the disclosed embodiments are a componentthereof.

In a networked deployment, the computer system 200 may operate in thecapacity of a server or as a client user computer in a client-serveruser network environment, or as a peer computer system in a peer-to-peer(or distributed) network environment. The computer system 200 can alsobe implemented as or incorporated into various devices, such as apersonal computer (PC), a tablet PC, a set-top box (STB), a personaldigital assistant (PDA), a mobile device, a palmtop computer, a laptopcomputer, a desktop computer, a communications device, a wirelesstelephone, a land-line telephone, a control system, a camera, a scanner,a facsimile machine, a printer, a pager, a personal trusted device, aweb appliance, a network router, switch or bridge, or any other machinecapable of executing a set of instructions (sequential or otherwise)that specify actions to be taken by that machine. In a particularembodiment, the computer system 200 can be implemented using electronicdevices that provide voice, video or data communication. Further, whilea single computer system 200 is illustrated, the term “system” shallalso be taken to include any collection of systems or sub-systems thatindividually or jointly execute a set, or multiple sets, of instructionsto perform one or more computer functions.

As illustrated in FIG. 2, the computer system 200 may include aprocessor 202, e.g., a central processing unit (CPU), a graphicsprocessing unit (GPU), or both. The processor 202 may be a component ina variety of systems. For example, the processor 202 may be part of astandard personal computer or a workstation. The processor 202 may beone or more general processors, digital signal processors, specificallyconfigured processors, application specific integrated circuits, fieldprogrammable gate arrays, servers, networks, digital circuits, analogcircuits, combinations thereof, or other now known or later developeddevices for analyzing and processing data. The processor 202 mayimplement a software program, such as code generated manually (i.e.,programmed).

The computer system 200 may include a memory 204 that can communicatevia a bus 208. The memory 204 may be a main memory, a static memory, ora dynamic memory. The memory 204 may include, but is not limited to,computer readable storage media such as various types of volatile andnon-volatile storage media, including but not limited to random accessmemory, read-only memory, programmable read-only memory, electricallyprogrammable read-only memory, electrically erasable read-only memory,flash memory, magnetic tape or disk, optical media and the like. In oneembodiment, the memory 204 includes a cache or random access memory forthe processor 202. In alternative embodiments, the memory 204 isseparate from the processor 202, such as a cache memory of a processor,the system memory, or other memory. The memory 204 may be an externalstorage device or database for storing data. Examples include a harddrive, compact disc (“CD”), digital video disc (“DVD”), memory card,memory stick, floppy disc, universal serial bus (“USB”) memory device,or any other device operative to store data. The memory 204 is operableto store instructions executable by the processor 202. The functions,acts or tasks illustrated in the figures or described herein may beperformed by the programmed processor 202 executing the instructions 212stored in the memory 204. The functions, acts or tasks are independentof the particular type of instructions set, storage media, processor orprocessing strategy and may be performed by software, hardware,integrated circuits, firm-ware, micro-code and the like, operating aloneor in combination. Likewise, processing strategies may includemultiprocessing, multitasking, parallel processing and the like.

As shown, the computer system 200 may further include a display unit214, such as a liquid crystal display (LCD), an organic light emittingdiode (OLED), a flat panel display, a solid state display, a cathode raytube (CRT), a projector, a printer or other now known or later developeddisplay device for outputting determined information. The display 214may act as an interface for the user to see the functioning of theprocessor 202, or specifically as an interface with the software storedin the memory 204 or in the drive unit 206.

Additionally, the computer system 200 may include an input device 216configured to allow a user to interact with any of the components ofsystem 200. The input device 216 may be a number pad, a keyboard, or acursor control device, such as a mouse, or a joystick, touch screendisplay, remote control or any other device operative to interact withthe system 200.

In a particular embodiment, as depicted in FIG. 2, the computer system200 may also include a disk or optical drive unit 206. The disk driveunit 206 may include a computer-readable medium 210 in which one or moresets of instructions 212, e.g., software, can be embedded. Further, theinstructions 212 may embody one or more of the methods or logic asdescribed herein. In a particular embodiment, the instructions 212 mayreside completely, or at least partially, within the memory 204 and/orwithin the processor 202 during execution by the computer system 200.The memory 204 and the processor 202 also may include computer-readablemedia as discussed herein.

The present disclosure contemplates a computer-readable medium thatincludes instructions 212 or receives and executes instructions 212responsive to a propagated signal, so that a device connected to anetwork 220 can communicate voice, video, audio, images or any otherdata over the network 220. Further, the instructions 212 may betransmitted or received over the network 220 via a communicationinterface 218. The communication interface 218 may be a part of theprocessor 202 or may be a separate component. The communicationinterface 218 may be created in software or may be a physical connectionin hardware. The communication interface 218 is configured to connectwith a network 220, external media, the display 214, or any othercomponents in system 200, or combinations thereof. The connection withthe network 220 may be a physical connection, such as a wired Ethernetconnection or may be established wirelessly. Likewise, the additionalconnections with other components of the system 200 may be physicalconnections or may be established wirelessly.

The network 220 may include wired networks, wireless networks, orcombinations thereof. The wireless network may be a cellular telephonenetwork, an 802.11, 802.16, 802.20, or WiMax network. Further, thenetwork 220 may be a public network, such as the Internet, a privatenetwork, such as an intranet, or combinations thereof, and may utilize avariety of networking protocols now available or later developedincluding, but not limited to, TCP/IP based networking protocols.

Embodiments of the subject matter and the functional operationsdescribed in this specification can be implemented in digital electroniccircuitry, or in computer software, firmware, or hardware, including thestructures disclosed in this specification and their structuralequivalents, or in combinations of one or more of them. Embodiments ofthe subject matter described in this specification can be implemented asone or more computer program products, i.e., one or more modules ofcomputer program instructions encoded on a computer readable medium forexecution by, or to control the operation of, data processing apparatus.While the computer-readable medium is shown to be a single medium, theterm “computer-readable medium” includes a single medium or multiplemedia, such as a centralized or distributed database, and/or associatedcaches and servers that store one or more sets of instructions. The term“computer-readable medium” shall also include any medium that is capableof storing, encoding or carrying a set of instructions for execution bya processor or that cause a computer system to perform any one or moreof the methods or operations disclosed herein. The computer readablemedium can be a machine-readable storage device, a machine-readablestorage substrate, a memory device, or a combination of one or more ofthem. The term “data processing apparatus” encompasses all apparatus,devices, and machines for processing data, including by way of example aprogrammable processor, a computer, or multiple processors or computers.The apparatus can include, in addition to hardware, code that creates anexecution environment for the computer program in question, e.g., codethat constitutes processor firmware, a protocol stack, a databasemanagement system, an operating system, or a combination of one or moreof them.

In a particular non-limiting, exemplary embodiment, thecomputer-readable medium can include a solid-state memory such as amemory card or other package that houses one or more non-volatileread-only memories. Further, the computer-readable medium can be arandom access memory or other volatile re-writable memory. Additionally,the computer-readable medium can include a magneto-optical or opticalmedium, such as a disk or tapes or other storage device to capturecarrier wave signals such as a signal communicated over a transmissionmedium. A digital file attachment to an e-mail or other self-containedinformation archive or set of archives may be considered a distributionmedium that is a tangible storage medium. Accordingly, the disclosure isconsidered to include any one or more of a computer-readable medium or adistribution medium and other equivalents and successor media, in whichdata or instructions may be stored.

In an alternative embodiment, dedicated or otherwise specificallyconfigured hardware implementations, such as application specificintegrated circuits, programmable logic arrays and other hardwaredevices, can be constructed to implement one or more of the methodsdescribed herein. Applications that may include the apparatus andsystems of various embodiments can broadly include a variety ofelectronic and computer systems. One or more embodiments describedherein may implement functions using two or more specific interconnectedhardware modules or devices with related control and data signals thatcan be communicated between and through the modules, or as portions ofan application-specific integrated circuit. Accordingly, the presentsystem encompasses software, firmware, and hardware implementations.

In accordance with various embodiments of the present disclosure, themethods described herein may be implemented by software programsexecutable by a computer system. Further, in an exemplary, non-limitedembodiment, implementations can include distributed processing,component/object distributed processing, and parallel processing.Alternatively, virtual computer system processing can be constructed toimplement one or more of the methods or functionality as describedherein.

Although the present specification describes components and functionsthat may be implemented in particular embodiments with reference toparticular standards and protocols, the invention is not limited to suchstandards and protocols. For example, standards for Internet and otherpacket switched network transmission (e.g., TCP/IP, UDP/IP, HTML, HTTP,HTTPS) represent examples of the state of the art. Such standards areperiodically superseded by faster or more efficient equivalents havingessentially the same functions. Accordingly, replacement standards andprotocols having the same or similar functions as those disclosed hereinare considered equivalents thereof.

A computer program (also known as a program, software, softwareapplication, script, or code) can be written in any form of programminglanguage, including compiled or interpreted languages, and it can bedeployed in any form, including as a standalone program or as a module,component, subroutine, or other unit suitable for use in a computingenvironment. A computer program does not necessarily correspond to afile in a file system. A program can be stored in a portion of a filethat holds other programs or data (e.g., one or more scripts stored in amarkup language document), in a single file dedicated to the program inquestion, or in multiple coordinated files (e.g., files that store oneor more modules, sub programs, or portions of code). A computer programcan be deployed to be executed on one computer or on multiple computersthat are located at one site or distributed across multiple sites andinterconnected by a communication network.

The processes and logic flows described in this specification can beperformed by one or more programmable processors executing one or morecomputer programs to perform functions by operating on input data andgenerating output. The processes and logic flows can also be performedby, and apparatus can also be implemented as, special purpose logiccircuitry, e.g., an FPGA (field programmable gate array) or an ASIC(application specific integrated circuit).

Processors suitable for the execution of a computer program include, byway of example, both general and special purpose microprocessors, andanyone or more processors of any kind of digital computer. Generally, aprocessor will receive instructions and data from a read only memory ora random access memory or both. The essential elements of a computer area processor for performing instructions and one or more memory devicesfor storing instructions and data. Generally, a computer will alsoinclude, or be operatively coupled to receive data from or transfer datato, or both, one or more mass storage devices for storing data, e.g.,magnetic, magneto optical disks, or optical disks. However, a computerneed not have such devices. Moreover, a computer can be embedded inanother device, e.g., a mobile telephone, a personal digital assistant(PDA), a mobile audio player, a Global Positioning System (GPS)receiver, to name just a few. Computer readable media suitable forstoring computer program instructions and data include all forms ofnon-volatile memory, media and memory devices, including by way ofexample semiconductor memory devices, e.g., EPROM, EEPROM, and flashmemory devices; magnetic disks, e.g., internal hard disks or removabledisks; magneto optical disks; and CD ROM and DVD-ROM disks. Theprocessor and the memory can be supplemented by, or incorporated in,special purpose logic circuitry.

As used herein, the terms “microprocessor” or “general-purposeprocessor” (“GPP”) may refer to a hardware device that fetchesinstructions and data from a memory or storage device and executes thoseinstructions (for example, an Intel Xeon processor or an AMD Opteronprocessor) to then, for example, process the data in accordancetherewith. The term “reconfigurable logic” may refer to any logictechnology whose form and function can be significantly altered (i.e.,reconfigured) in the field post-manufacture as opposed to amicroprocessor, whose function can change post-manufacture, e.g. viacomputer executable software code, but whose form, e.g. thearrangement/layout and interconnection of logical structures, is fixedat manufacture. The term “software” may refer to data processingfunctionality that is deployed on a GPP. The term “firmware” may referto data processing functionality that is deployed on reconfigurablelogic. One example of a reconfigurable logic is a field programmablegate array (“FPGA”) which is a reconfigurable integrated circuit. AnFPGA may contain programmable logic components called “logic blocks”,and a hierarchy of reconfigurable interconnects that allow the blocks tobe “wired together”, somewhat like many (changeable) logic gates thatcan be inter-wired in (many) different configurations. Logic blocks maybe configured to perform complex combinatorial functions, or merelysimple logic gates like AND, OR, NOT and XOR. An FPGA may furtherinclude memory elements, which may be simple flip-flops or more completeblocks of memory.

To provide for interaction with a user, embodiments of the subjectmatter described in this specification can be implemented on a devicehaving a display, e.g., a CRT (cathode ray tube) or LCD (liquid crystaldisplay) monitor, for displaying information to the user and a keyboardand a pointing device, e.g., a mouse or a trackball, by which the usercan provide input to the computer. Other kinds of devices can be used toprovide for interaction with a user as well. Feedback provided to theuser can be any form of sensory feedback, e.g., visual feedback,auditory feedback, or tactile feedback. Input from the user can bereceived in any form, including acoustic, speech, or tactile input.

Embodiments of the subject matter described in this specification can beimplemented in a computing system that includes a back end component,e.g., a data server, or that includes a middleware component, e.g., anapplication server, or that includes a front end component, e.g., aclient computer having a graphical user interface or a Web browserthrough which a user can interact with an implementation of the subjectmatter described in this specification, or any combination of one ormore such back end, middleware, or front end components. The componentsof the system can be interconnected by any form or medium of digitaldata communication, e.g., a communication network. Examples ofcommunication networks include a local area network (“LAN”) and a widearea network (“WAN”), e.g., the Internet.

The computing system can include clients and servers. A client andserver are generally remote from each other and typically interactthrough a communication network. The relationship of client and serverarises by virtue of computer programs running on the respectivecomputers and having a client-server relationship to each other.

It should be appreciated that the disclosed embodiments may beapplicable to other types of messages depending upon the implementation.Further, the messages may comprise one or more data packets, datagramsor other collection of data formatted, arranged configured and/orpackaged in a particular one or more protocols, e.g., the FIX protocol,TCP/IP, Ethernet, etc., suitable for transmission via a network 214 aswas described, such as the message format and/or protocols described inU.S. Pat. No. 7,831,491 and U.S. Patent Publication No. 2005/0096999 A1,both of which are incorporated by reference herein in their entiretiesand relied upon. Further, the disclosed message management system may beimplemented using an open message standard implementation, such as FIX,FIX Binary, FIX/FAST, or by an exchange-provided API.

The embodiments described may herein utilize trade related electronicmessages such as mass quote messages, individual order messages,modification messages, cancellation messages, etc., so as to enacttrading activity in an electronic market. The trading entity and/ormarket participant may have one or multiple trading terminals associatedwith the session. Furthermore, the financial instruments may befinancial derivative products. Derivative products may include futurescontracts, options on futures contracts, futures contracts that arefunctions of or related to other futures contracts, swaps, swaptions, orother financial instruments that have their price related to or derivedfrom an underlying product, security, commodity, equity, index, orinterest rate product. In one embodiment, the orders are for optionscontracts that belong to a common option class. Orders may also be forbaskets, quadrants, other combinations of financial instruments, etc.The option contracts may have a plurality of strike prices and/orcomprise put and call contracts. A mass quote message may be received atan exchange. As used herein, an exchange computing system 100 includes aplace or system that receives and/or executes orders.

In an embodiment, a plurality of electronic messages is received fromthe network. The plurality of electronic messages may be received at anetwork interface for the electronic trading system. The plurality ofelectronic messages may be sent from market participants. The pluralityof messages may include order characteristics and be associated withactions to be executed with respect to an order that may be extractedfrom the order characteristics. The action may involve any action asassociated with transacting the order in an electronic trading system.The actions may involve placing the orders within a particular marketand/or order book of a market in the electronic trading system.

In an embodiment, the market may operate using characteristics thatinvolve collecting orders over a period of time, such as a batch auctionmarket. In such an embodiment, the period of time may be considered anorder accumulation period. The period of time may involve a beginningtime and an ending time, with orders placed in the market after thebeginning time, and the placed order matched at or after the endingtime. As such, the action associated with an order extracted from amessage may involve placing the order in the market within the period oftime. Also, electronic messages may be received prior to or after thebeginning time of the period of time.

The electronic messages may also include other data relating to theorder. In an embodiment, the other data may be data indicating aparticular time in which the action is to be executed. As such, theorder may be considered a temporally specific order. The particular timein which an action is undertaken may be established with respect to anymeasure of absolute or relative time. In an embodiment, the time inwhich an action is undertaken may be established with reference to thebeginning time of the time period or ending time of the time period in abatch auction embodiment. For example, the particular time may be aspecific amount of time, such as 10 milliseconds, prior to the endingtime of an order accumulation period in the batch auction. Further, theorder accumulation period may involve dissecting the accumulation periodinto multiple consecutive, overlapping, or otherwise divided,sub-periods of time. For example, the sub-periods may involve distincttemporal windows within the order accumulation period. As such, theparticular time may be an indicator of a particular temporal windowduring the accumulation period. For example, the particular time may bespecified as the last temporal window prior to the ending time of theaccumulation period.

In an embodiment, the electronic message may also include other actionsto be taken with respect to the order. These other actions may beactions to be executed after the initial or primary action associatedwith the order. For example, the actions may involve modifying orcanceling an already placed order. Further, in an embodiment, the otherdata may indicate order modification characteristics. For example, theother data may include a price or volume change in an order. The otheractions may involve modifying the already placed order to align with theorder modification characteristics, such as changing the price or volumeof the already placed order.

In an embodiment, other actions may be dependent actions. For example,the execution of the actions may involve a detection of an occurrence ofan event. Such triggering events may be described as other data in theelectronic message. For example, the triggering event may be a releaseof an economic statistic from an organization relating to a productbeing bought or sold in the electronic market, a receipt of pricinginformation from a correlated electronic market, a detection of a changein market sentiment derived from identification of keywords in socialmedia or public statements of officials related to a product beingbought or sold in the electronic market, and/or any other event orcombination of events which may be detected by an electronic tradingsystem.

In an embodiment, the action, or a primary action, associated with anorder may be executed. For example, an order extracted from electronicmessage order characteristics may be placed into a market, or anelectronic order book for a market, such that the order may be matchedwith other orders counter thereto.

In an embodiment involving a market operating using batch auctionprinciples, the action, such as placing the order, may be executedsubsequent to the beginning time of the order accumulation period, butprior to the ending time of the order accumulation period. Further, asindicated above, a message may also include other information for theorder, such as a particular time the action is to be executed. In suchan embodiment, the action may be executed at the particular time. Forexample, in an embodiment involving a batch auction process havingsub-periods during an order accumulation period, an order may be placedduring a specified sub-period of the order accumulation period. Thedisclosed embodiments may be applicable to batch auction processing, aswell as continuous processing.

Also, it may be noted that messages may be received prior or subsequentto the beginning time of an order accumulation period. Orders extractedfrom messages received prior to the beginning time may have theassociated actions, or primary actions such as placing the order,executed at any time subsequent to the beginning time, but prior to theending time, of the order accumulation period when no particular timefor the execution is indicated in the electronic message. In anembodiment, messages received prior to the beginning time but not havinga particular time specified will have the associated action executed assoon as possible after the beginning time. Because of this, specifying atime for order action execution may allow a distribution and moredefinite relative time of order placement so as to allow resources ofthe electronic trading system to operate more efficiently.

In an embodiment, the execution of temporally specific messages may becontrolled by the electronic trading system such that a limited ormaximum number may be executed in any particular accumulation period, orsub-period. In an embodiment, the order accumulation time periodinvolves a plurality of sub-periods involving distinct temporal windows,a particular time indicated by a message may be indicative of aparticular temporal window of the plurality of temporal windows, and theexecution of the at least one temporally specific message is limited tothe execution of a specified sub-period maximum number of temporallyspecific messages during a particular sub-period. The electronic tradingsystem may distribute the ability to submit temporally specific messageto selected market participants. For example, only five temporallyspecific messages may be allowed in any one particular period orsub-period. Further, the ability to submit temporally specific messageswithin particular periods or sub-periods may be distributed based on anytechnique. For example, the temporally specific messages for aparticular sub-period may be auctioned off or otherwise sold by theelectronic trading system to market participants. Also, the electronictrading system may distribute the temporally specific messages topreferred market participants, or as an incentive to participate in aparticular market.

In an embodiment, an event occurrence may be detected. The eventoccurrence may be the occurrence of an event that was specified as otherinformation relating to an order extracted from an electronic message.The event may be a triggering event for a modification or cancellationaction associated with an order. The event may be detected subsequent tothe execution of the first action when an electronic message furthercomprises the data representative of the event and a secondary actionassociated with the order. In an embodiment involving a market operatingon batch auction principles, the event may be detected subsequent to theexecution of a first action, placing an order, but prior to the endingtime of an order accumulation period in which the action was executed.

In an embodiment, other actions associated with an order may beexecuted. The other actions may be any action associated with an order.For example, the action may be a conditional action that is executed inresponse to a detection of an occurrence of an event. Further, in amarket operating using batch auction principles, the conditional actionmay be executed after the placement of an order during an orderaccumulation period, but in response to a detection of an occurrence ofan event prior to an ending time of the order accumulation period. Insuch an embodiment, the conditional action may be executed prior to theending time of the order accumulation period. For example, the placedorder may be canceled, or modified using other provided ordercharacteristics in the message, in response to the detection of theoccurrence of the event.

An event may be a release of an economic statistic or a fluctuation ofprices in a correlated market. An event may also be a perceptible changein market sentiment of a correlated market. A change may be perceptiblebased on a monitoring of orders or social media for keywords inreference to the market in question. For example, electronic tradingsystems may be configured to be triggered for action by a use ofkeywords during a course of ongoing public statements of officials whomay be in a position to impact markets, such as Congressional testimonyof the Chairperson of the Federal Reserve System.

The other or secondary action may also be considered a modification of afirst action executed with respect to an order. For example, acancellation may be considered a cancellation of the placement of theorder. Further, a secondary action may have other data in the messagewhich indicates a specific time in which the secondary action may beexecuted. The specific time may be a time relative to a first action, orplacement of the order, or relative to an accumulation period in a batchauction market. For example, the specific time for execution of thesecondary action may be at a time specified relative and prior to theending period of the order accumulation period. Further, multiplesecondary actions may be provided for a single order. Also, with eachsecondary action a different triggering event may be provided.

In an embodiment, an incoming transaction may be received. The incomingtransaction may be from, and therefore associated with, a marketparticipant of an electronic market managed by an electronic tradingsystem. The transaction may involve an order as extracted from areceived message, and may have an associated action. The actions mayinvolve placing an order to buy or sell a financial product in theelectronic market, or modifying or deleting such an order. In anembodiment, the financial product may be based on an associatedfinancial instrument which the electronic market is established totrade.

In an embodiment, the action associated with the transaction isdetermined. For example, it may be determined whether the incomingtransaction comprises an order to buy or sell a quantity of theassociated financial instrument or an order to modify or cancel anexisting order in the electronic market. Orders to buy or sell andorders to modify or cancel may be acted upon differently by theelectronic market. For example, data indicative of differentcharacteristics of the types of orders may be stored.

In an embodiment, data relating to the received transaction is stored.The data may be stored in any device, or using any technique, operableto store and provide recovery of data. For example, a memory 204 orcomputer readable medium 210, may be used to store data, as is describedwith respect to FIG. 2 in further detail herein. Data may be storedrelating received transactions for a period of time, indefinitely, orfor a rolling most recent time period such that the stored data isindicative of the market participant's recent activity in the electronicmarket.

If and/or when a transaction is determined to be an order to modify orcancel a previously placed, or existing, order, data indicative of theseactions may be stored. For example, data indicative of a running countof a number or frequency of the receipt of modify or cancel orders fromthe market participant may be stored. A number may be a total number ofmodify or cancel orders received from the market participant, or anumber of modify or cancel orders received from the market participantover a specified time. A frequency may be a time based frequency, as ina number of cancel or modify orders per unit of time, or a number ofcancel or modify orders received from the market participant as apercentage of total transactions received from the participant, whichmay or may not be limited by a specified length of time.

If and/or when a transaction is determined to be an order to buy or sella financial product, or financial instrument, other indicative data maybe stored. For example, data indicative of quantity and associated priceof the order to buy or sell may be stored.

Data indicative of attempts to match incoming orders may also be stored.The data may be stored in any device, or using any technique, operableto store and provide recovery of data. For example, a memory 204 orcomputer readable medium 210, may be used to store data, as is describedwith respect to FIG. 2. The acts of the process as described herein mayalso be repeated. As such, data for multiple received transactions formultiple market participants may be stored and used as describe herein.

The order processing module 118 may also store data indicative ofcharacteristics of the extracted orders. For example, the orderprocessing module may store data indicative of orders having anassociated modify or cancel action, such as by recording a count of thenumber of such orders associated with particular market participants.The order processing module may also store data indicative of quantitiesand associated prices of orders to buy or sell a product placed in themarket order book 110, as associated with particular marketparticipants.

Also, the order processing module 118 may be configured to calculate andassociate with particular orders a value indicative of an associatedmarket participant's market activity quality, which is a valueindicative of whether the market participant's market activity increasesor tends to increase liquidity of a market. This value may be determinedbased on the price of the particular order, previously stored quantitiesof orders from the associated market participant, the previously storeddata indicative of previously received orders to modify or cancel asassociated with the market participant, and previously stored dataindicative of a result of the attempt to match previously receivedorders stored in association with the market participant. The orderprocessing module 118 may determine or otherwise calculate scoresindicative of the quality value based on these stored extracted ordercharacteristics, such as an MQI as described herein.

Further, electronic trading systems may perform actions on orders placedfrom received messages based on various characteristics of the messagesand/or market participants associated with the messages. These actionsmay include matching the orders either during a continuous auctionprocess, or at the conclusion of a collection period during a batchauction process. The matching of orders may be by any technique.

The matching of orders may occur based on a priority indicated by thecharacteristics of orders and market participants associated with theorders. Orders having a higher priority may be matched before orders ofa lower priority. Such priority may be determined using varioustechniques. For example, orders that were indicated by messages receivedearlier may receive a higher priority to match than orders that wereindicated by messages received later. Also, scoring or grading of thecharacteristics may provide for priority determination. Data indicativeof order matches may be stored by a match engine and/or an orderprocessing module 118, and used for determining MQI scores of marketparticipants.

Example Users

Generally, a market may involve market makers, such as marketparticipants who consistently provide bids and/or offers at specificprices in a manner typically conducive to balancing risk, and markettakers who may be willing to execute transactions at prevailing bids oroffers may be characterized by more aggressive actions so as to maintainrisk and/or exposure as a speculative investment strategy. From analternate perspective, a market maker may be considered a marketparticipant who places an order to sell at a price at which there is nopreviously or concurrently provided counter order. Similarly, a markettaker may be considered a market participant who places an order to buyat a price at which there is a previously or concurrently providedcounter order. A balanced and efficient market may involve both marketmakers and market takers, coexisting in a mutually beneficial basis. Themutual existence, when functioning properly, may facilitate liquidity inthe market such that a market may exist with “tight” bid-ask spreads(e.g., small difference between bid and ask prices) and a “deep” volumefrom many currently provided orders such that large quantity orders maybe executed without driving prices significantly higher or lower.

As such, both market participant types are useful in generatingliquidity in a market, but specific characteristics of market activitytaken by market participants may provide an indication of a particularmarket participant's effect on market liquidity. For example, a MarketQuality Index (“MQI”) of an order may be determined using thecharacteristics. An MQI may be considered a value indicating alikelihood that a particular order will improve or facilitate liquidityin a market. That is, the value may indicate a likelihood that the orderwill increase a probability that subsequent requests and transactionfrom other market participants will be satisfied. As such, an MQI may bedetermined based on a proximity of the entered price of an order to amidpoint of a current bid-ask price spread, a size of the entered order,a volume or quantity of previously filled orders of the marketparticipant associated with the order, and/or a frequency ofmodifications to previous orders of the market participant associatedwith the order. In this way, an electronic trading system may functionto assess and/or assign an MQI to received electronic messages toestablish messages that have a higher value to the system, and thus thesystem may use computing resources more efficiently by expendingresources to match orders of the higher value messages prior toexpending resources of lower value messages.

While an MQI may be applied to any or all market participants, such anindex may also be applied only to a subset thereof, such as large marketparticipants, or market participants whose market activity as measuredin terms of average daily message traffic over a limited historical timeperiod exceeds a specified number. For example, a market participantgenerating more than 500, 1,000, or even 10,000 market messages per daymay be considered a large market participant.

An exchange provides one or more markets for the purchase and sale ofvarious types of products including financial instruments such asstocks, bonds, futures contracts, options, currency, cash, and othersimilar instruments. Agricultural products and commodities are alsoexamples of products traded on such exchanges. A futures contract is aproduct that is a contract for the future delivery of another financialinstrument such as a quantity of grains, metals, oils, bonds, currency,or cash. Generally, each exchange establishes a specification for eachmarket provided thereby that defines at least the product traded in themarket, minimum quantities that must be traded, and minimum changes inprice (e.g., tick size). For some types of products (e.g., futures oroptions), the specification further defines a quantity of the underlyingproduct represented by one unit (or lot) of the product, and deliveryand expiration dates. As will be described, the exchange may furtherdefine the matching algorithm, or rules, by which incoming orders willbe matched/allocated to resting orders.

Matching and Transaction Processing

Market participants, e.g., traders, use software to send orders ormessages to the trading platform. The order identifies the product, thequantity of the product the trader wishes to trade, a price at which thetrader wishes to trade the product, and a direction of the order (i.e.,whether the order is a bid, i.e., an offer to buy, or an ask, i.e., anoffer to sell). It will be appreciated that there may be other ordertypes or messages that traders can send including requests to modify orcancel a previously submitted order.

The exchange computer system monitors incoming orders received therebyand attempts to identify, i.e., match or allocate, as described herein,one or more previously received, but not yet matched, orders, i.e.,limit orders to buy or sell a given quantity at a given price, referredto as “resting” orders, stored in an order book database, wherein eachidentified order is contra to the incoming order and has a favorableprice relative to the incoming order. An incoming order may be an“aggressor” order, i.e., a market order to sell a given quantity atwhatever may be the current resting bid order price(s) or a market orderto buy a given quantity at whatever may be the current resting ask orderprice(s). An incoming order may be a “market making” order, i.e., amarket order to buy or sell at a price for which there are currently noresting orders. In particular, if the incoming order is a bid, i.e., anoffer to buy, then the identified order(s) will be an ask, i.e., anoffer to sell, at a price that is identical to or higher than the bidprice. Similarly, if the incoming order is an ask, i.e., an offer tosell, the identified order(s) will be a bid, i.e., an offer to buy, at aprice that is identical to or lower than the offer price.

An exchange computing system may receive conditional orders or messagesfor a data object, where the order may include two prices or values: areference value and a stop value. A conditional order may be configuredso that when a product represented by the data object trades at thereference price, the stop order is activated at the stop value. Forexample, if the exchange computing system's order management moduleincludes a stop order with a stop price of 5 and a limit price of 1 fora product, and a trade at 5 (i.e., the stop price of the stop order)occurs, then the exchange computing system attempts to trade at 1 (i.e.,the limit price of the stop order). In other words, a stop order is aconditional order to trade (or execute) at the limit price that istriggered (or elected) when a trade at the stop price occurs.

Stop orders also rest on, or are maintained in, an order book to monitorfor a trade at the stop price, which triggers an attempted trade at thelimit price. In some embodiments, a triggered limit price for a stoporder may be treated as an incoming order.

Upon identification (matching) of a contra order(s), a minimum of thequantities associated with the identified order and the incoming orderis matched and that quantity of each of the identified and incomingorders become two halves of a matched trade that is sent to a clearinghouse. The exchange computer system considers each identified order inthis manner until either all of the identified orders have beenconsidered or all of the quantity associated with the incoming order hasbeen matched, i.e., the order has been filled. If any quantity of theincoming order remains, an entry may be created in the order bookdatabase and information regarding the incoming order is recordedtherein, i.e., a resting order is placed on the order book for theremaining quantity to await a subsequent incoming order counter thereto.

It should be appreciated that in electronic trading systems implementedvia an exchange computing system, a trade price (or match value) maydiffer from (i.e., be better for the submitter, e.g., lower than asubmitted buy price or higher than a submitted sell price) the limitprice that is submitted, e.g., a price included in an incoming message,or a triggered limit price from a stop order.

As used herein, “better” than a reference value means lower than thereference value if the transaction is a purchase (or acquire)transaction, and higher than the reference value if the transaction is asell transaction. Said another way, for purchase (or acquire)transactions, lower values are better, and for relinquish or selltransactions, higher values are better.

Traders access the markets on a trading platform using trading softwarethat receives and displays at least a portion of the order book for amarket, i.e., at least a portion of the currently resting orders,enables a trader to provide parameters for an order for the producttraded in the market, and transmits the order to the exchange computersystem. The trading software typically includes a graphical userinterface to display at least a price and quantity of some of theentries in the order book associated with the market. The number ofentries of the order book displayed is generally preconfigured by thetrading software, limited by the exchange computer system, or customizedby the user. Some graphical user interfaces display order books ofmultiple markets of one or more trading platforms. The trader may be anindividual who trades on his/her behalf, a broker trading on behalf ofanother person or entity, a group, or an entity. Furthermore, the tradermay be a system that automatically generates and submits orders.

If the exchange computer system identifies that an incoming market ordermay be filled by a combination of multiple resting orders, e.g., theresting order at the best price only partially fills the incoming order,the exchange computer system may allocate the remaining quantity of theincoming, i.e., that which was not filled by the resting order at thebest price, among such identified orders in accordance withprioritization and allocation rules/algorithms, referred to as“allocation algorithms” or “matching algorithms,” as, for example, maybe defined in the specification of the particular financial product ordefined by the exchange for multiple financial products. Similarly, ifthe exchange computer system identifies multiple orders contra to theincoming limit order and that have an identical price which is favorableto the price of the incoming order, i.e., the price is equal to orbetter, e.g., lower if the incoming order is a buy (or instruction topurchase, or instruction to acquire) or higher if the incoming order isa sell (or instruction to relinquish), than the price of the incomingorder, the exchange computer system may allocate the quantity of theincoming order among such identified orders in accordance with thematching algorithms as, for example, may be defined in the specificationof the particular financial product or defined by the exchange formultiple financial products.

An exchange responds to inputs, such as trader orders, cancellation,etc., in a manner as expected by the market participants, such as basedon market data, e.g., prices, available counter-orders, etc., to providean expected level of certainty that transactions will occur in aconsistent and predictable manner and without unknown or unascertainablerisks. Accordingly, the method by which incoming orders are matched withresting orders must be defined so that market participants have anexpectation of what the result will be when they place an order or haveresting orders and an incoming order is received, even if the expectedresult is, in fact, at least partially unpredictable due to somecomponent of the process being random or arbitrary or due to marketparticipants having imperfect or less than all information, e.g.,unknown position of an order in an order book. Typically, the exchangedefines the matching/allocation algorithm that will be used for aparticular financial product, with or without input from the marketparticipants. Once defined for a particular product, thematching/allocation algorithm is typically not altered, except inlimited circumstance, such as to correct errors or improve operation, soas not to disrupt trader expectations. It will be appreciated thatdifferent products offered by a particular exchange may use differentmatching algorithms.

For example, a first-in/first-out (FIFO) matching algorithm, alsoreferred to as a “Price Time” algorithm, considers each identified ordersequentially in accordance with when the identified order was received.The quantity of the incoming order is matched to the quantity of theidentified order at the best price received earliest, then quantities ofthe next earliest best price orders, and so on until the quantity of theincoming order is exhausted. Some product specifications define the useof a pro-rata matching algorithm, wherein a quantity of an incomingorder is allocated to each of plurality of identified ordersproportionally. Some exchange computer systems provide a priority tocertain standing orders in particular markets. An example of such anorder is the first order that improves a price (i.e., improves themarket) for the product during a trading session. To be given priority,the trading platform may require that the quantity associated with theorder is at least a minimum quantity. Further, some exchange computersystems cap the quantity of an incoming order that is allocated to astanding order on the basis of a priority for certain markets. Inaddition, some exchange computer systems may give a preference to orderssubmitted by a trader who is designated as a market maker for theproduct. Other exchange computer systems may use other criteria todetermine whether orders submitted by a particular trader are given apreference. Typically, when the exchange computer system allocates aquantity of an incoming order to a plurality of identified orders at thesame price, the trading host allocates a quantity of the incoming orderto any orders that have been given priority. The exchange computersystem thereafter allocates any remaining quantity of the incoming orderto orders submitted by traders designated to have a preference, and thenallocates any still remaining quantity of the incoming order using theFIFO or pro-rata algorithms. Pro-rata algorithms used in some marketsmay require that an allocation provided to a particular order inaccordance with the pro-rata algorithm must meet at least a minimumallocation quantity. Any orders that do not meet or exceed the minimumallocation quantity are allocated to on a FIFO basis after the pro-rataallocation (if any quantity of the incoming order remains). Moreinformation regarding order allocation may be found in U.S. Pat. No.7,853,499, the entirety of which is incorporated by reference herein andrelied upon.

Other examples of matching algorithms which may be defined forallocation of orders of a particular financial product include: PriceExplicit Time; Order Level Pro Rata; Order Level Priority Pro Rata;Preference Price Explicit Time; Preference Order Level Pro Rata;Preference Order Level Priority Pro Rata; Threshold Pro-Rata; PriorityThreshold Pro-Rata; Preference Threshold Pro-Rata; Priority PreferenceThreshold Pro-Rata; and Split Price-Time Pro-Rata.

For example, the Price Explicit Time trading policy is based on thebasic Price Time trading policy with Explicit Orders having priorityover Implied Orders at the same price level. The order of traded volumeallocation at a single price level may therefore be: Explicit order witholdest timestamp first; followed by any remaining explicit orders intimestamp sequence (First In, First Out—FIFO) next; followed by impliedorder with oldest timestamp next; followed by any remaining impliedorders in timestamp sequence (FIFO).

In Order Level Pro Rata, also referred to as Price Pro Rata, priority isgiven to orders at the best price (highest for a bid, lowest for anoffer). If there are several orders at this best price, equal priorityis given to every order at this price and incoming business is dividedamong these orders in proportion to their order size. The Pro Ratasequence of events is: 1. Extract all potential matching orders at bestprice from the order book into a list. 2. Sort the list by order size,largest order size first. If equal order sizes, oldest timestamp first.This is the matching list. 3. Find the ‘Matching order size, which isthe total size of all the orders in the matching list. 4. Find the‘tradable volume’, which is the smallest of the matching volume and thevolume left to trade on the incoming order. 5. Allocate volume to eachorder in the matching list in turn, starting at the beginning of thelist. If all the tradable volume gets used up, orders near the end ofthe list may not get allocation. 6. The amount of volume to allocate toeach order is given by the formula: (Order volume/Matchingvolume)*Tradable volume. The result is rounded down (for example,21.99999999 becomes 21) unless the result is less than 1, when itbecomes 1. 7. If tradable volume remains when the last order in the listhad been allocated to, return to step 3. Note: The matching list is notre-sorted, even though the volume has changed. The order whichoriginally had the largest volume is still at the beginning of the list.8. If there is still volume left to trade on the incoming order, repeatthe entire algorithm at the next price level.

Order Level Priority Pro Rata, also referred to as Threshold Pro Rata,is similar to the Price (or ‘Vanilla’) Pro Rata algorithm but has avolume threshold defined. Any pro rata allocation below the thresholdwill be rounded down to 0. The initial pass of volume allocation iscarried out in using pro rata; the second pass of volume allocation iscarried out using Price Explicit Time. The Threshold Pro Rata sequenceof events is: 1. Extract all potential matching orders at best pricefrom the order book into a list. 2. Sort the list by explicit timepriority, oldest timestamp first. This is the matching list. 3. Find the‘Matching volume’, which is the total volume of all the orders in thematching list. 4. Find the ‘tradable volume’, which is the smallest ofthe matching volume and the volume left to trade on the incoming order.5. Allocate volume to each order in the matching list in turn, startingat the beginning of the list. 6. The amount of volume to allocate toeach order is given by the formula: (Order volume/Matchingvolume)*Tradable volume. The result is rounded down to the nearest lot(for example, 21.99999999 becomes 21) unless the result is less than thedefined threshold in which case it is rounded down to 0. 7. If tradablevolume remains when the last order in the list had been allocated to,the remaining volume is allocated in time priority to the matching list.8. If there is still volume left to trade on the incoming order, repeatthe entire algorithm at the next price level.

In the Split Price Time Pro-Rata algorithms, a Price Time Percentageparameter is defined. This percentage of the matching volume at eachprice is allocated by the Price Explicit Time algorithm and theremainder is allocated by the Threshold Pro-Rata algorithm. There arefour variants of this algorithm, with and without Priority and/orPreference. The Price Time Percentage parameter is an integer between 1and 99. (A percentage of zero would be equivalent to using therespective existing Threshold Pro-Rata algorithm, and a percentage of100 would be equivalent to using the respective existing Price Timealgorithm). The Price Time Volume will be the residual incoming volume,after any priority and/or Preference allocation has been made,multiplied by the Price Time Percentage. Fractional parts will berounded up, so the Price Time Volume will always be at least 1 lot andmay be the entire incoming volume. The Price Time Volume is allocated toresting orders in strict time priority. Any remaining incoming volumeafter the Price Time Volume has been allocated will be allocatedaccording to the respective Threshold Pro-Rata algorithm. The sequenceof allocation, at each price level, is therefore: 1. Priority order, ifapplicable. 2. Preference allocation, if applicable. 3. Price Timeallocation of the configured percentage of incoming volume. 4. ThresholdPro-Rata allocation of any remaining incoming volume. 5. Finalallocation of any leftover lots in time sequence. Any resting order mayreceive multiple allocations from the various stages of the algorithm.

It will be appreciated that there may be other allocation algorithms,including combinations of algorithms, now available or later developed,which may be utilized with the disclosed embodiments, and all suchalgorithms are contemplated herein. In one embodiment, the disclosedembodiments may be used in any combination or sequence with theallocation algorithms described herein.

One exemplary system for matching is described in U.S. patentapplication Ser. No. 13/534,499, filed on Jun. 27, 2012, entitled“Multiple Trade Matching Algorithms,” published as U.S. PatentApplication Publication No. 2014/0006243 A1, the entirety of which isincorporated by reference herein and relied upon, which discloses anadaptive match engine which draws upon different matching algorithms,e.g., the rules which dictate how a given order should be allocatedamong qualifying resting orders, depending upon market conditions, toimprove the operation of the market. For example, for a financialproduct, such as a futures contract, having a future expiration date,the match engine may match incoming orders according to one algorithmwhen the remaining time to expiration is above a threshold, recognizingthat during this portion of the life of the contract, the market forthis product is likely to have high volatility. However, as theremaining time to expiration decreases, volatility may decrease.Accordingly, when the remaining time to expiration falls below thethreshold, the match engine switches to a different match algorithmwhich may be designed to encourage trading relative to the decliningtrading volatility. Thereby, by conditionally switching among matchingalgorithms within the same financial product, as will be described, thedisclosed match engine may automatically adapt to the changing marketconditions of a financial product, e.g., a limited life product, in anon-preferential manner, maintaining fair order allocation whileimproving market liquidity, e.g., over the life of the product.

In one implementation, the system may evaluate market conditions on adaily basis and, based thereon, change the matching algorithm betweendaily trading sessions, i.e., when the market is closed, such that whenthe market reopens, a new trading algorithm is in effect for theparticular product. The system may facilitate more frequent changes tothe matching algorithms so as to dynamically adapt to changing marketconditions, e.g., intra-day changes, and even intra-order matchingchanges. It will be further appreciated that hybrid matching algorithms,which match part of an order using one algorithm and another part of theorder using a different algorithm, may also be used.

With respect to incoming orders, some traders, such as automated and/oralgorithmic traders, attempt to respond to market events, such as tocapitalize upon a mispriced resting order or other market inefficiency,as quickly as possible. This may result in penalizing the trader whomakes an errant trade, or whose underlying trading motivations havechanged, and who cannot otherwise modify or cancel their order fasterthan other traders can submit trades there against. It may consideredthat an electronic trading system that rewards the trader who submitstheir order first creates an incentive to either invest substantialcapital in faster trading systems, participate in the marketsubstantially to capitalize on opportunities (aggressor side/lower risktrading) as opposed to creating new opportunities (market making/higherrisk trading), modify existing systems to streamline business logic atthe cost of trade quality, or reduce one's activities and exposure inthe market. The result may be a lesser quality market and/or reducedtransaction volume, and corresponding thereto, reduced fees to theexchange.

With respect to resting orders, allocation/matching suitable restingorders to match against an incoming order can be performed, as describedherein, in many different ways. Generally, it will be appreciated thatallocation/matching algorithms are only needed when the incoming orderquantity is less than the total quantity of the suitable resting ordersas, only in this situation, is it necessary to decide which restingorder(s) will not be fully satisfied, which trader(s) will not get theirorders filled. It can be seen from the above descriptions of thematching/allocation algorithms, that they fall generally into threecategories: time priority/first-in-first-out (“FIFO”), pro rata, or ahybrid of FIFO and pro rata.

FIFO generally rewards the first trader to place an order at aparticular price and maintains this reward indefinitely. So if a traderis the first to place an order at price X, no matter how long that orderrests and no matter how many orders may follow at the same price, assoon as a suitable incoming order is received, that first trader will bematched first. This “first mover” system may commit other traders topositions in the queue after the first move traders. Furthermore, whileit may be beneficial to give priority to a trader who is first to placean order at a given price because that trader is, in effect, taking arisk, the longer that the trader's order rests, the less beneficial itmay be. For instance, it could deter other traders from adding liquidityto the marketplace at that price because they know the first mover (andpotentially others) already occupies the front of the queue.

With a pro rata allocation, incoming orders are effectively split amongsuitable resting orders. This provides a sense of fairness in thateveryone may get some of their order filled. However, a trader who tooka risk by being first to place an order (a “market turning” order) at aprice may end up having to share an incoming order with a much latersubmitted order. Furthermore, as a pro rata allocation distributes theincoming order according to a proportion based on the resting orderquantities, traders may place orders for large quantities, which theyare willing to trade but may not necessarily want to trade, in order toincrease the proportion of an incoming order that they will receive.This results in an escalation of quantities on the order book andexposes a trader to a risk that someone may trade against one of theseorders and subject the trader to a larger trade than they intended. Inthe typical case, once an incoming order is allocated against theselarge resting orders, the traders subsequently cancel the remainingresting quantity which may frustrate other traders. Accordingly, as FIFOand pro rata both have benefits and problems, exchanges may try to usehybrid allocation/matching algorithms which attempt to balance thesebenefits and problems by combining FIFO and pro rata in some manner.However, hybrid systems define conditions or fixed rules to determinewhen FIFO should be used and when pro rata should be used. For example,a fixed percentage of an incoming order may be allocated using a FIFOmechanism with the remainder being allocated pro rata.

Spread Instruments

Traders trading on an exchange including, for example, exchange computersystem 100, often desire to trade multiple financial instruments incombination. Each component of the combination may be called a leg.Traders can submit orders for individual legs or in some cases cansubmit a single order for multiple financial instruments in anexchange-defined combination. Such orders may be called a strategyorder, a spread order, or a variety of other names.

A spread instrument may involve the simultaneous purchase of onesecurity and sale of a related security, called legs, as a unit. Thelegs of a spread instrument may be options or futures contracts, orcombinations of the two. Trades in spread instruments are executed toyield an overall net position whose value, called the spread, depends onthe difference between the prices of the legs. Spread instruments may betraded in an attempt to profit from the widening or narrowing of thespread, rather than from movement in the prices of the legs directly.Spread instruments are either “bought” or “sold” depending on whetherthe trade will profit from the widening or narrowing of the spread,respectively. An exchange often supports trading of common spreads as aunit rather than as individual legs, thus ensuring simultaneousexecution of the two legs, eliminating the execution risk of one legexecuting but the other failing.

One example of a spread instrument is a calendar spread instrument. Thelegs of a calendar spread instrument differ in delivery date of theunderlier. The leg with the earlier occurring delivery date is oftenreferred to as the lead month contract. A leg with a later occurringdelivery date is often referred to as a deferred month contract. Anotherexample of a spread instrument is a butterfly spread instrument, whichincludes three legs having different delivery dates. The delivery datesof the legs may be equidistant to each other. The counterparty ordersthat are matched against such a combination order may be individual,“outright” orders or may be part of other combination orders.

In other words, an exchange may receive, and hold or let rest on thebooks, outright orders for individual contracts as well as outrightorders for spreads associated with the individual contracts. An outrightorder (for either a contract or for a spread) may include an outrightbid or an outright offer, although some outright orders may bundle manybids or offers into one message (often called a mass quote).

A spread is an order for the price difference between two contracts.This results in the trader holding a long and a short position in two ormore related futures or options on futures contracts, with the objectiveof profiting from a change in the price relationship. A typical spreadproduct includes multiple legs, each of which may include one or moreunderlying financial instruments. A butterfly spread product, forexample, may include three legs. The first leg may consist of buying afirst contract. The second leg may consist of selling two of a secondcontract. The third leg may consist of buying a third contract. Theprice of a butterfly spread product may be calculated as:

Butterfly=Leg1−2×Leg2+Leg3  (equation 1)

In the above equation, Leg1 equals the price of the first contract, Leg2equals the price of the second contract and Leg3 equals the price of thethird contract. Thus, a butterfly spread could be assembled from twointer-delivery spreads in opposite directions with the center deliverymonth common to both spreads.

A calendar spread, also called an intra-commodity spread, for futures isan order for the simultaneous purchase and sale of the same futurescontract in different contract months (i.e., buying a September CME S&P500® futures contract and selling a December CME S&P 500 futurescontract).

A crush spread is an order, usually in the soybean futures market, forthe simultaneous purchase of soybean futures and the sale of soybeanmeal and soybean oil futures to establish a processing margin. A crackspread is an order for a specific spread trade involving simultaneouslybuying and selling contracts in crude oil and one or more derivativeproducts, typically gasoline and heating oil. Oil refineries may trade acrack spread to hedge the price risk of their operations, whilespeculators attempt to profit from a change in the oil/gasoline pricedifferential.

A straddle is an order for the purchase or sale of an equal number ofputs and calls, with the same strike price and expiration dates. A longstraddle is a straddle in which a long position is taken in both a putand a call option. A short straddle is a straddle in which a shortposition is taken in both a put and a call option. A strangle is anorder for the purchase of a put and a call, in which the options havethe same expiration and the put strike is lower than the call strike,called a long strangle. A strangle may also be the sale of a put and acall, in which the options have the same expiration and the put strikeis lower than the call strike, called a short strangle. A pack is anorder for the simultaneous purchase or sale of an equally weighted,consecutive series of four futures contracts, quoted on an average netchange basis from the previous day's settlement price. Packs provide areadily available, widely accepted method for executing multiple futurescontracts with a single transaction. A bundle is an order for thesimultaneous sale or purchase of one each of a series of consecutivefutures contracts. Bundles provide a readily available, widely acceptedmethod for executing multiple futures contracts with a singletransaction.

Implication

Thus an exchange may match outright orders, such as individual contractsor spread orders (which as discussed herein could include multipleindividual contracts). The exchange may also imply orders from outrightorders. For example, exchange computer system 100 may derive, identifyand/or advertise, publish, display or otherwise make available fortrading orders based on outright orders.

As was described above, the financial instruments which are the subjectof the orders to trade, may include one or more component financialinstruments. While each financial instrument may have its own orderbook, i.e. market, in which it may be traded, in the case of a financialinstrument having more than one component financial instrument, thosecomponent financial instruments may further have their own order booksin which they may be traded. Accordingly, when an order for a financialinstrument is received, it may be matched against a suitable counterorder in its own order book or, possibly, against a combination ofsuitable counter orders in the order books the component financialinstruments thereof, or which share a common component financialinstrument. For example, an order for a spread contract comprisingcomponent financial instruments A and B may be matched against anothersuitable order for that spread contract. However, it may also be matchedagainst suitable separate counter orders for the A and for the Bcomponent financial instruments found in the order books therefore.Similarly, if an order for the A contract is received and suitable matchcannot be found in the A order book, it may be possible to match orderfor A against a combination of a suitable counter order for a spreadcontract comprising the A and B component financial instruments and asuitable counter order for the B component financial instrument. This isreferred to as “implication” where a given order for a financialinstrument may be matched via a combination of suitable counter ordersfor financial instruments which share common, or otherwiseinterdependent, component financial instruments. Implication increasesthe liquidity of the market by providing additional opportunities fororders to be traded. Increasing the number of transactions may furtherincrease the number of transaction fees collected by the electronictrading system.

The order for a particular financial instrument actually received from amarket participant, whether it comprises one or more component financialinstruments, is referred to as a “real” or “outright” order, or simplyas an outright. The one or more orders which must be synthesized andsubmitted into order books other than the order book for the outrightorder in order to create matches therein, are referred to as “implied”orders. Upon receipt of an incoming order, the identification orderivation of suitable implied orders which would allow at least apartial trade of the incoming outright order to be executed is referredto as “implication” or “implied matching”, the identified orders beingreferred to as an “implied match.” Depending on the number componentfinancial instruments involved, and whether those component financialinstruments further comprise component financial instruments of theirown, there may be numerous different implied matches identified whichwould allow the incoming order to be at least partially matched andmechanisms may be provided to arbitrate, e.g., automatically, amongthem, such as by picking the implied match comprising the least numberof component financial instruments or the least number of synthesizedorders.

Upon receipt of an incoming order, or thereafter, a combination of oneor more suitable/hypothetical counter orders which have not actuallybeen received but if they were received, would allow at least a partialtrade of the incoming order to be executed, may be, e.g., automatically,identified or derived and referred to as an “implied opportunity.” Aswith implied matches, there may be numerous implied opportunitiesidentified for a given incoming order. Implied opportunities areadvertised to the market participants, such as via suitable syntheticorders, e.g. counter to the desired order, being placed on therespective order books to rest (or give the appearance that there is anorder resting) and presented via the market data feed, electronicallycommunicated to the market participants, to appear available to trade inorder to solicit the desired orders from the market participants.Depending on the number component financial instruments involved, andwhether those component financial instruments further comprise componentfinancial instruments of their own, there may be numerous impliedopportunities, the submission of a counter order in response thereto,would allow the incoming order to be at least partially matched.

Implied opportunities, e.g. the advertised synthetic orders, mayfrequently have better prices than the corresponding real orders in thesame contract. This can occur when two or more traders incrementallyimprove their order prices in the hope of attracting a trade, sincecombining the small improvements from two or more real orders can resultin a big improvement in their combination. In general, advertisingimplied opportunities at better prices will encourage traders to enterthe opposing orders to trade with them. The more implied opportunitiesthat the match engine of an electronic trading system cancalculate/derive, the greater this encouragement will be and the morethe Exchange will benefit from increased transaction volume. However,identifying implied opportunities may be computationally intensive. In ahigh performance trading system where low transaction latency isimportant, it may be important to identify and advertise impliedopportunities quickly so as to improve or maintain market participantinterest and/or market liquidity.

For example, two different outright orders may be resting on the books,or be available to trade or match. The orders may be resting becausethere are no outright orders that match the resting orders. Thus, eachof the orders may wait or rest on the books until an appropriateoutright counteroffer comes into the exchange or is placed by a user ofthe exchange. The orders may be for two different contracts that onlydiffer in delivery dates. It should be appreciated that such orderscould be represented as a calendar spread order. Instead of waiting fortwo appropriate outright orders to be placed that would match the twoexisting or resting orders, the exchange computer system may identify ahypothetical spread order that, if entered into the system as a tradablespread order, would allow the exchange computer system to match the twooutright orders. The exchange may thus advertise or make available aspread order to users of the exchange system that, if matched with atradable spread order, would allow the exchange to also match the tworesting orders. Thus, the match engine is configured to detect that thetwo resting orders may be combined into an order in the spreadinstrument and accordingly creates an implied order.

In other words, the exchange's matching system may imply thecounteroffer order by using multiple orders to create the counterofferorder. Examples of spreads include implied IN, implied OUT, 2nd- ormultiple-generation, crack spreads, straddle, strangle, butterfly, andpack spreads. Implied IN spread orders are derived from existingoutright orders in individual legs. Implied OUT outright orders arederived from a combination of an existing spread order and an existingoutright order in one of the individual underlying legs. Implied orderscan fill in gaps in the market and allow spreads and outright futurestraders to trade in a product where there would otherwise have beenlittle or no available bids and asks.

For example, implied IN spreads may be created from existing outrightorders in individual contracts where an outright order in a spread canbe matched with other outright orders in the spread or with acombination of orders in the legs of the spread. An implied OUT spreadmay be created from the combination of an existing outright order in aspread and an existing outright order in one of the individualunderlying leg. An implied IN or implied OUT spread may be created whenan electronic match system simultaneously works synthetic spread ordersin spread markets and synthetic orders in the individual leg marketswithout the risk to the trader/broker of being double filled or filledon one leg and not on the other leg.

By linking the spread and outright markets, implied spread tradingincreases market liquidity. For example, a buy in one contract month andan offer in another contract month in the same futures contract cancreate an implied market in the corresponding calendar spread. Anexchange may match an order for a spread product with another order forthe spread product. Some existing exchanges attempt to match orders forspread products with multiple orders for legs of the spread products.With such systems, every spread product contract is broken down into acollection of legs and an attempt is made to match orders for the legs.

Implied orders, unlike real orders, are generated by electronic tradingsystems. In other words, implied orders are computer generated ordersderived from real orders. The system creates the “derived” or “implied”order and provides the implied order as a market that may be tradedagainst. If a trader trades against this implied order, then the realorders that combined to create the implied order and the resultingmarket are executed as matched trades. Implied orders generally increaseoverall market liquidity. The creation of implied orders increases thenumber of tradable items, which has the potential of attractingadditional traders. Exchanges benefit from increased transaction volume.Transaction volume may also increase as the number of matched tradeitems increases.

Examples of implied spread trading include those disclosed in U.S.Patent Publication No. 2005/0203826, entitled “Implied Spread TradingSystem,” the entire disclosure of which is incorporated by referenceherein and relied upon. Examples of implied markets include thosedisclosed in U.S. Pat. No. 7,039,610, entitled “Implied Market TradingSystem,” the entire disclosure of which is incorporated by referenceherein and relied upon.

In some cases, the outright market for the deferred month or otherconstituent contract may not be sufficiently active to provide marketdata (e.g., bid-offer data) and/or trade data. Spread instrumentsinvolving such contracts may nonetheless be made available by theexchange. The market data from the spread instruments may then be usedto determine a settlement price for the constituent contract. Thesettlement price may be determined, for example, through a boundaryconstraint-based technique based on the market data (e.g., bid-offerdata) for the spread instrument, as described in U.S. Patent PublicationNo. 2015/0073962 entitled “Boundary Constraint-Based Settlement inSpread Markets” (“the '962 Publication”), the entire disclosure of whichis incorporated by reference herein and relied upon. Settlement pricedetermination techniques may be implemented to cover calendar monthspread instruments having different deferred month contracts.

Order Book Object Data Structures

In one embodiment, the messages and/or values received for each objectmay be stored in queues according to value and/or priority techniquesimplemented by an exchange computing system 100. FIG. 3A illustrates anexample data structure 300, which may be stored in a memory or otherstorage device, such as the memory 204 or storage device 206 describedwith respect to FIG. 2, for storing and retrieving messages related todifferent values for the same action for an object. For example, datastructure 300 may be a set of queues or linked lists for multiple valuesfor an action, e.g., bid, on an object. Data structure 300 may beimplemented as a database. It should be appreciated that the system maystore multiple values for the same action for an object, for example,because multiple users submitted messages to buy specified quantities ofan object at different values. Thus, in one embodiment, the exchangecomputing system may keep track of different orders or messages forbuying or selling quantities of objects at specified values.

Although the application contemplates using queue data structures forstoring messages in a memory, the implementation may involve additionalpointers, i.e., memory address pointers, or linking to other datastructures. Incoming messages may be stored at an identifiable memoryaddress. The transaction processor can traverse messages in order bypointing to and retrieving different messages from the differentmemories. Thus, messages that may be depicted sequentially, e.g., inFIG. 3B below, may actually be stored in memory in disparate locations.The software programs implementing the transaction processing mayretrieve and process messages in sequence from the various disparate(e.g., random) locations. Thus, in one embodiment, each queue may storedifferent values, which could represent prices, where each value pointsto or is linked to the messages (which may themselves be stored inqueues and sequenced according to priority techniques, such asprioritizing by value) that will match at that value. For example, asshown in FIG. 3A, all of the values relevant to executing an action atdifferent values for an object are stored in a queue. Each value in turnpoints to, e.g., a linked list or queue logically associated with thevalues. The linked list stores the messages that instruct the exchangecomputing system to buy specified quantities of the object at thecorresponding value.

The sequence of the messages in the message queues connected to eachvalue may be determined by exchange implemented priority techniques. Forexample, in FIG. 3A, messages M1, M2, M3 and M4 are associated withperforming an action (e.g., buying or selling) a certain number of units(may be different for each message) at Value 1. M1 has priority over M2,which has priority over M3, which has priority over M4. Thus, if acounter order matches at Value 1, the system fills as much quantity aspossible associated with M1 first, then M2, then M3, and then M4.

In the illustrated examples, the values may be stored in sequentialorder, and the best or lead value for a given queue may be readilyretrievable by and/or accessible to the disclosed system. Thus, in oneembodiment, the value having the best priority may be illustrated asbeing in the topmost position in a queue, although the system may beconfigured to place the best priority message in some otherpredetermined position. In the example of FIG. 3A, Value 1 is shown asbeing the best value or lead value, or the top of the book value, for anexample Action.

FIG. 3B illustrates an example alternative data structure 350 forstoring and retrieving messages and related values. It should beappreciated that matches occur based on values, and so all the messagesrelated to a given value may be prioritized over all other messagesrelated to a different value. As shown in FIG. 3B, the messages may bestored in one queue and grouped by values according to the hierarchy ofthe values. The hierarchy of the values may depend on the action to beperformed.

For example, if a queue is a sell queue (e.g., the Action is Sell), thelowest value may be given the best priority and the highest value may begiven the lowest priority. Thus, as shown in FIG. 3B, if Value 1 islower than Value 2 which is lower than Value 3, Value 1 messages may beprioritized over Value 2, which in turn may be prioritized over Value 3.

Within Value 1, M1 is prioritized over M2, which in turn is prioritizedover M3, which in turn is prioritized over M4. Within Value 2, M5 isprioritized over M6, which in turn is prioritized over M7, which in turnis prioritized over M8. Within Value 3, M9 is prioritized over M10,which in turn is prioritized over M11, which in turn is prioritized overM12.

Alternatively, the messages may be stored in a tree-node data structurethat defines the priorities of the messages. In one embodiment, themessages may make up the nodes.

A lead acquisition value may be the best or lead value in an acquisitionqueue of an order book object, and a lead relinquish value may be thebest or lead value in a relinquish queue of the order book object.

In one embodiment, the system may traverse through a number of differentvalues and associated messages when processing an incoming message.Traversing values may involve the processor loading each value, checkingthat value and deciding whether to load another value, i.e., byaccessing the address pointed at by the address pointer value. Inparticular, referring to FIG. 3B, if the queue is for selling an objectfor the listed Values 1, 2 and 3 (where Value 1 is lower than Value 2which is lower than Value 3), and if the system receives an incomingaggressing order to buy quantity X at a Value 4 that is greater thanValues 1, 2, and 3, the system will fill as much of quantity X aspossible by first traversing through the messages under Value 1 (insequence M1, M2, M3, M4). If any of the quantity of X remains, thesystem traverses down the prioritized queue until all of the incomingorder is filled (e.g., all of X is matched) or until all of thequantities of M1 through M12 are filled. Any remaining, unmatchedquantity remains on the books, e.g., as a resting order at Value 4,which was the entered value or the message's value.

The system may traverse the queues and check the values in a queue, andupon finding the appropriate value, may locate the messages involved inmaking that value available to the system. When an outright messagevalue is stored in a queue, and when that outright message is involvedin a trade or match, the system may check the queue for the value, andthen may check the data structure storing messages associated with thatvalue.

In one embodiment, an exchange computing system may convert allfinancial instruments to objects. In one embodiment, an object mayrepresent the order book for a financial instrument. Moreover, in oneembodiment, an object may be defined by two queues, one queue for eachaction that can be performed by a user on the object. For example, anorder book converted to an object may be represented by an Ask queue anda Bid queue. Resting messages or orders associated with the respectivefinancial instrument may be stored in the appropriate queue and recalledtherefrom.

In one embodiment, the messages associated with objects may be stored inspecific ways depending on the characteristics of the various messagesand the states of the various objects in memory. For example, a systemmay hold certain resting messages in queue until the message is to beprocessed, e.g., the message is involved in a match. The order, sequenceor priority given to messages may depend on the characteristics of themessage. For example, in certain environments, messages may indicate anaction that a computer in the system should perform. Actions may becomplementary actions, or require more than one message to complete. Forexample, a system may be tasked with matching messages or actionscontained within messages. The messages that are not matched may bequeued by the system in a data queue or other structure, e.g., a datatree having nodes representing messages or orders.

The queues are structured so that the messages are stored in sequenceaccording to priority. Although the embodiments are disclosed as beingimplemented in queues, it should be understood that different datastructures such as for example linked lists or trees may also be used.

The system may include separate data structures, e.g., queues, fordifferent actions associated with different objects within the system.For example, in one embodiment, the system may include a queue for eachpossible action that can be performed on an object. The action may beassociated with a value. The system prioritizes the actions based inpart on the associated value.

For example, as shown in FIG. 3C, the order book module of a computingsystem may include several paired queues, such as queues Bid and Ask foran object 302 (e.g., Object A). The system may include two queues, orone pair of queues, for each object that is matched or processed by thesystem. In one embodiment, the system stores messages in the queues thathave not yet been matched or processed. FIG. 3C may be an implementationof the data structures disclosed in FIGS. 3A and/or 3B. Each queue mayhave a top of book, or lead, position, such as positions 304 and 306,which stores data that is retrievable.

The queues may define the priority or sequence in which messages areprocessed upon a match event. For example, two messages stored in aqueue may represent performing the same action at the same value. When athird message is received by the system that represents a matchingaction at the same value, the system may need to select one of the twowaiting, or resting, messages as the message to use for a match. Thus,when multiple messages can be matched at the same value, the exchangemay have a choice or some flexibility regarding the message that ismatched. The queues may define the priority in which orders that areotherwise equivalent (e.g., same action for the same object at the samevalue) are processed.

The system may include a pair of queues for each object, e.g., a bid andask queue for each object. Each queue may be for example implementedutilizing the data structure of FIG. 3B. The exchange may be able tospecify the conditions upon which a message for an object should beplaced in a queue. For example, the system may include one queue foreach possible action that can be performed on an object. The system maybe configured to process messages that match with each other. In oneembodiment, a message that indicates performing an action at a value maymatch with a message indicating performing a corresponding action at thesame value. Or, the system may determine the existence of a match whenmessages for the same value exist in both queues of the same object. Themessages may be received from the same or different users or traders.

The queues illustrated in FIG. 3C hold or store messages received by acomputing exchange, e.g., messages submitted by a user to the computingexchange, and waiting for a proper match. It should be appreciated thatthe queues may also hold or store implieds, e.g., implied messagesgenerated by the exchange system, such as messages implied in or impliedout as described herein. The system thus adds messages to the queues asthey are received, e.g., messages submitted by users, or generated,e.g., implied messages generated by the exchanges. The sequence orprioritization of messages in the queues is based on information aboutthe messages and the overall state of the various objects in the system.

When the data transaction processing system is implemented as anexchange computing system, as discussed above, different clientcomputers submit electronic data transaction request messages to theexchange computing system. Electronic data transaction request messagesinclude requests to perform a transaction on a data object, e.g., at avalue for a quantity. The exchange computing system includes atransaction processor, e.g., a hardware matching processor or matchengine, that matches, or attempts to match, pairs of messages with eachother. For example, messages may match if they contain counterinstructions (e.g., one message includes instructions to buy, the othermessage includes instructions to sell) for the same product at the samevalue. In some cases, depending on the nature of the message, the valueat which a match occurs may be the submitted value or a better value. Abetter value may mean higher or lower value depending on the specifictransaction requested. For example, a buy order may match at thesubmitted buy value or a lower (e.g., better) value. A sell order maymatch at the submitted sell value or a higher (e.g., better) value.

Transaction Processor Data Structures

FIG. 4 illustrates an example embodiment of a data structure used toimplement match engine module 106. Match engine module 106 may include aconversion component 402, pre-match queue 404, match component 406,post-match queue 408 and publish component 410.

Although the embodiments are disclosed as being implemented in queues,it should be understood that different data structures, such as forexample linked lists or trees, may also be used. Although theapplication contemplates using queue data structures for storingmessages in a memory, the implementation may involve additionalpointers, i.e., memory address pointers, or linking to other datastructures. Thus, in one embodiment, each incoming message may be storedat an identifiable memory address. The transaction processing componentscan traverse messages in order by pointing to and retrieving differentmessages from the different memories. Thus, messages that may beprocessed sequentially in queues may actually be stored in memory indisparate locations. The software programs implementing the transactionprocessing may retrieve and process messages in sequence from thevarious disparate (e.g., random) locations.

The queues described herein may, in one embodiment, be structured sothat the messages are stored in sequence according to time of receipt,e.g., they may be first in first out (FIFO) queues.

The match engine module 106 may be an example of a transactionprocessing system. The pre-match queue 404 may be an example of apre-transaction queue. The match component 406 may be an example of atransaction component. The post-match queue 408 may be an example of apost-transaction queue. The publish component 410 may be an example of adistribution component. The transaction component may process messagesand generate transaction component results.

In one embodiment, the publish component may be a distribution componentthat can distribute data to one or more market participant computers. Inone embodiment, match engine module 106 operates according to a firstin, first out (FIFO) ordering. The conversion component 402 converts orextracts a message received from a trader via the Market Segment Gatewayor MSG into a message format that can be input into the pre-match queue404.

Messages from the pre-match queue may enter the match component 406sequentially and may be processed sequentially. In one regard, thepre-transaction queue, e.g., the pre-match queue, may be considered tobe a buffer or waiting spot for messages before they can enter and beprocessed by the transaction component, e.g., the match component. Thematch component matches orders, and the time a messages spends beingprocessed by the match component can vary, depending on the contents ofthe message and resting orders on the book. Thus, newly receivedmessages wait in the pre-transaction queue until the match component isready to process those messages. Moreover, messages are received andprocessed sequentially or in a first-in, first-out FIFO methodology. Thefirst message that enters the pre-match or pre-transaction queue will bethe first message to exit the pre-match queue and enter the matchcomponent. In one embodiment, there is no out-of-order messageprocessing for messages received by the transaction processing system.The pre-match and post-match queues are, in one embodiment, fixed insize, and any messages received when the queues are full may need towait outside the transaction processing system or be re-sent to thetransaction processing system.

The match component 406 processes an order or message, at which pointthe transaction processing system may consider the order or message ashaving been processed. The match component 406 may generate one messageor more than one message, depending on whether an incoming order wassuccessfully matched by the match component. An order message thatmatches against a resting order in the order book may generate dozens orhundreds of messages. For example, a large incoming order may matchagainst several smaller resting orders at the same price level. Forexample, if many orders match due to a new order message, the matchengine needs to send out multiple messages informing traders whichresting orders have matched. Or, an order message may not match anyresting order and only generate an acknowledgement message. Thus, thematch component 406 in one embodiment will generate at least onemessage, but may generate more messages, depending upon the activitiesoccurring in the match component. For example, the more orders that arematched due to a given message being processed by the match component,the more time may be needed to process that message. Other messagesbehind that given message will have to wait in the pre-match queue.

Messages resulting from matches in the match component 406 enter thepost-match queue 408. The post-match queue may be similar infunctionality and structure to the pre-match queue discussed above,e.g., the post-match queue is a FIFO queue of fixed size. As illustratedin FIG. 4, a difference between the pre- and post-match queues may bethe location and contents of the structures, namely, the pre-match queuestores messages that are waiting to be processed, whereas the post-matchqueue stores match component results due to matching by the matchcomponent. The match component receives messages from the pre-matchqueue, and sends match component results to the post-match queue. In oneembodiment, the time that results messages, generated due to thetransaction processing of a given message, spend in the post-match queueis not included in the latency calculation for the given message.

Messages from the post-match queue 408 enter the publish component 410sequentially and are published via the MSG sequentially. Thus, themessages in the post-match queue 408 are an effect or result of themessages that were previously in the pre-match queue 404. In otherwords, messages that are in the pre-match queue 404 at any given timewill have an impact on or affect the contents of the post-match queue408, depending on the events that occur in the match component 406 oncethe messages in the pre-match queue 404 enter the match component 406.

As noted above, the match engine module 106 in one embodiment operatesin a first in first out (FIFO) scheme. In other words, the first messagethat enters the match engine module 106 is the first message that isprocessed by the match engine module 106. Thus, the match engine module106 in one embodiment processes messages in the order the messages arereceived. In FIG. 4, as shown by the data flow arrow, data is processedsequentially by the illustrated structures from left to right, beginningat the conversion component 402, to the pre-match queue, to the matchcomponent 406, to the post-match queue 408, and to the publish component410. The overall transaction processing system operates in a FIFO schemesuch that data flows from element 402 to 404 to 406 to 408 to 410, inthat order. If any one of the queues or components of the transactionprocessing system experiences a delay, that creates a backlog for thestructures preceding the delayed structure. For example, if the match ortransaction component is undergoing a high processing volume, and if thepre-match or pre-transaction queue is full of messages waiting to enterthe match or transaction component, the conversion component may not beable to add any more messages to the pre-match or pre-transaction queue.

Messages wait in the pre-match queue. The time a message waits in thepre-match queue depends upon how many messages are ahead of that message(i.e., earlier messages), and how much time each of the earlier messagesspends being serviced or processed by the match component. Messages alsowait in the post-match queue. The time a message waits in the post-matchqueue depends upon how many messages are ahead of that message (i.e.,earlier messages), and how much time each of the earlier messages spendsbeing serviced or processed by the publish component. These wait timesmay be viewed as a latency that can affect a market participant'strading strategy.

After a message is published (after being processed by the componentsand/or queues of the match engine module), e.g., via a market data feed,the message becomes public information and is publically viewable andaccessible. Traders consuming such published messages may act upon thosemessage, e.g., submit additional new input messages to the exchangecomputing system responsive to the published messages.

The match component attempts to match aggressing or incoming ordersagainst resting orders. If an aggressing order does not match anyresting orders, then the aggressing order may become a resting order, oran order resting on the books. For example, if a message includes a neworder that is specified to have a one-year time in force, and the neworder does not match any existing resting order, the new order willessentially become a resting order to be matched (or attempted to bematched) with some future aggressing order. The new order will thenremain on the books for one year. On the other hand, an order specifiedas a fill or kill (e.g., if the order cannot be filled or matched withan order currently resting on the books, the order should be canceled)will never become a resting order, because it will either be filled ormatched with a currently resting order, or it will be canceled. Theamount of time needed to process or service a message once that messagehas entered the match component may be referred to as a service time.The service time for a message may depend on the state of the orderbooks when the message enters the match component, as well as thecontents, e.g., orders, that are in the message.

In one embodiment, orders in a message are considered to be “locked in”,or processed, or committed, upon reaching and entering the matchcomponent. If the terms of the aggressing order match a resting orderwhen the aggressing order enters the match component, then theaggressing order will be in one embodiment guaranteed to match.

As noted above, the latency experienced by a message, or the amount oftime a message spends waiting to enter the match component, depends uponhow many messages are ahead of that message (i.e., earlier messages),and how much time each of the earlier messages spends being serviced orprocessed by the match component. The amount of time a match componentspends processing, matching or attempting to match a message dependsupon the type of message, or the characteristics of the message. Thetime spent inside the processor may be considered to be a service time,e.g., the amount of time a message spends being processed or serviced bythe processor.

The number of matches or fills that may be generated in response to anew order message for a financial instrument will depend on the state ofthe data object representing the electronic marketplace for thefinancial instrument. The state of the match engine can change based onthe contents of incoming messages.

It should be appreciated that the match engine's overall latency is inpart a result of the match engine processing the messages it receives.The match component's service time may be a function of the message type(e.g., new, modify, cancel), message arrival rate (e.g., how many ordersor messages is the match engine module receiving, e.g., messages persecond), message arrival time (e.g., the time a message hits the inboundMSG or market segment gateway), number of fills generated (e.g., howmany fills were generated due to a given message, or how many ordersmatched due to an aggressing or received order), or number of Mass Quoteentries (e.g., how many of the entries request a mass quote).

In one embodiment, the time a message spends:

Being converted in the conversion component 402 may be referred to as aconversion time;

Waiting in the pre-match queue 404 may be referred to as a wait untilmatch time;

Being processed or serviced in the match component 406 may be referredto as a matching time;

Waiting in the post-match queue 408 may be referred to as a wait untilpublish time; and

Being processed or published via the publish component 410 may bereferred to as a publishing time.

It should be appreciated that the latency may be calculated, in oneembodiment, as the sum of the conversion time and wait until match time.Or, the system may calculate latency as the sum of the conversion time,wait until match time, matching time, wait until publish time, andpublishing time. In systems where some or all of those times arenegligible, or consistent, a measured latency may only include the sumof some of those times. Or, a system may be designed to only calculateone of the times that is the most variable, or that dominates (e.g.,percentage wise) the overall latency. For example, some marketparticipants may only care about how long a newly sent message that isadded to the end of the pre-match queue will spend waiting in thepre-match queue. Other market participants may care about how long thatmarket participant will have to wait to receive an acknowledgement fromthe match engine that a message has entered the match component. Yetother market participants may care about how much time will pass fromwhen a message is sent to the match engine's conversion component towhen match component results exit or egress from the publish component.

The speed at which trades are executed through electronic tradingsystems provide many benefits. Electronic trading systems can facilitatea large number of market transactions. The greater the number of markettransactions, the greater a market's liquidity. In liquid markets,prices are driven by competition, prices reflect a consensus of aninvestment's value, and trading systems provide a free and opendissemination of information. With the advent of improved computationaland communications capabilities, the speed and efficiency with whichtraders may receive information and trade in electronic trading systemshas greatly improved. Algorithmic and high frequency trading utilizecomputers to quickly analyze market information and place tradesallowing traders to take advantage of even the smallest movements inprices.

Such improved speed and efficiency also increases the speed at whichproblems may occur and propagate, such as where the market ceases tooperate as intended, i.e., the market no longer reflects a trueconsensus of the value of traded products among the market participants.Such problems are typically evidenced by extreme market activity such aslarge and/or rapid changes in price, whether up or down, over a shortperiod of time, or an extreme volume of trades taking place.

In particular, traders, whether human or electronic, may not alwaysreact in a rational manner, such as when presented with imperfectinformation, when acting in fraudulent or otherwise unethical manner,and/or due to faulty training or design. For example, whilecommunications technologies may have improved, inequities in access toinformation and opportunities to participate still exist, which may ormay not be in compliance with legislative, regulatory and/or ethicalrules, e.g., some traders receive information before other traders, orsome traders may be able to process received information and/or placetrader orders more quickly than others. In many cases, irrational traderbehavior may be triggered by a market event, such as a change in price,creating a feedback loop where the initial irrational reaction may thencause further market events, such as a continued price drop, triggeringfurther irrational behavior and an extreme change in the price of thetraded product in a short period of time. High speed trading exacerbatesthe problem as there may be little time for traders, or those overseeingthem, to contemplate their reactions and/or take corrective actionbefore significant losses may be incurred. Furthermore, improvedcommunications among traders facilitates propagation of irrationalbehavior in one market to other markets as traders in those othermarkets react to the results of the irrational behavior.

To mitigate risk and ensure a fair and balanced market, electronictrading systems often provide mechanisms to rapidly detect and respondto situations where a market is not operating in a fair and balancedmanner or otherwise where the market value is not reflective of a trueconsensus of the value of the traded products among the marketparticipants. However, transaction integrity modules typically compriseintensive computing routines that increase latency and processing timeto an exchange computing system.

Transaction integrity modules rapidly evaluate message values todetermine whether newly received messages should be subject to marketprotecting integrity modules. For example, the disclosed embodiments mayrely upon or leverage previous determinations to determine whether newlyreceived messages should be processed through the transaction integritymodule pipeline, or should instead bypass the transaction integritymodule. When applied to electronic trading systems, the disclosedembodiments may be implemented as an optimization processor thatcontinually and automatically processes incoming messages.

The transaction integrity modules associated with an exchange computingsystem scan for, rapidly detect and respond to extreme changes, eitherup (“spike”) or down (“dip”) in the market where a precipitous marketmove/change occurs. If an unacceptable message is detected, transactionintegrity modules may respond by taking an action, e.g., a corrective orresponsive action, such as notifying the operator of the exchange, suchas the Global Control Center (“GCC”) of the Chicago Mercantile Exchange(“CME”), placing the market in a paused or reserved state, described inmore detail below, establishing permanent or temporary trade pricelimitations, or other actions, or combinations thereof, to mitigate theeffects of the extreme change, so as to, for example, slow down themarket or otherwise allow traders time to adequately analyze and reactto market conditions, and subsequently submitting more messages/ordersthat can be used to better determine a true consensus.

In a futures market that has few resting orders but many stop orders, anorder executed at a limit price can cause a cascading execution of buyor sell stop orders. The triggering and election of these stop orderscan seem almost instantaneous lowering the value of a market in just afew seconds. A problem may occur when one or more trades bring many stoporders into the market. A fast execution of these stop orders mayprevent opposite side orders from entering the market, preventing buyersfrom competing against other buyers and sellers from competing againstother sellers. “Stop Price Logic” systems exist to handle extreme marketchanges due to an undesirable execution of stop orders. See, forexample, U.S. Pat. Nos. 8,103,576 and 8,112,347 and U.S. PatentPublication No. 2005/0108141 A1, herein incorporated by reference intheir entireties and relied upon.

Some systems focus on the speed of the movement of the market, anddetect when a market for a particular product moves too quickly, eitherup or down, in too short a period of time, e.g., the velocity of themarket exceeds a defined threshold limit. See, for example, U.S. Pat.No. 8,660,936, entitled “Detection and mitigation of effects of highvelocity price changes” (“the '936 Patent”), the entire disclosure ofwhich is incorporated by reference herein and relied upon.

U.S. patent application Ser. No. 15/091,763 entitled “Multi-Path RoutingSystem Including An Integrity Mechanism”, the entirety of which isincorporated by reference herein and relied upon, describes a routingsystem that rapidly determines whether messages received by a datatransaction processing system related to data objects in a computingsystem should be routed through or bypass integrity modules designed todetect and mitigate undesirable object conditions.

Electronic Data Multiple Transaction Request Messages

FIG. 5A illustrates an example electronic data multiple transactionrequest message 500, which includes multiple electronic data transactionrequests 504 (order 1), 514 (order 2), and 524 (order 3). For example,each electronic data transaction request may be an order requesting theexchange computing system perform an action. The electronic datamultiple transaction request message 500 may include a mass order IDfield 502, which can be used to refer to the group of orders orelectronic data transaction requests in electronic data multipletransaction request message 500. Each order, or electronic datatransaction request, in electronic data multiple transaction requestmessage 500 includes a financial instrument field (e.g., fields 506,516, and 526 in orders 1, 2 and 3, respectively), a type field (e.g.,fields 508, 518, and 528 in orders 1, 2 and 3, respectively), a valuefield (e.g., fields 510, 520, and 530 in orders 1, 2 and 3,respectively), and a quantity field (e.g., fields 512, 522, and 5326 inorders 1, 2 and 3, respectively).

When implemented in an exchange computing system that enables trading offinancial instruments, the electronic data multiple transaction requestmessage may be referred to as a mass order, and may include a mass orderidentifier, or a mass order ID field, e.g., field 502. In oneembodiment, the electronic data multiple transaction request messageprepared and submitted by the client computer may not include a massorder identifier. The exchange computing system, upon receipt of theelectronic data multiple transaction request message, may detect that anincoming message is an electronic data multiple transaction requestmessage (e.g., because it includes multiple different orders, orelectronic data transaction requests), and assign a mass orderidentifier to the electronic data multiple transaction request message.Thus, the mass order ID may be assigned by the sender (e.g., the userassociated with the sending client computer) prior to or upontransmission, or assigned by the exchange computing system upon receiptof the electronic data multiple transaction request message.

The electronic data multiple transaction request message includesdifferent electronic data transaction requests that may be associatedwith different financial instruments, or may be associated withdifferent values or prices for the same financial instrument. Forexample, FIG. 5A illustrates a data object 540, which represents orderbook object 1, and data object 560, which represents order book object2.

Value 510 in order 1 and value 520 in order 2 both relate to differentsides/types of order book object 1. Thus, orders 1 and 2 both relate tothe same financial instrument, and may accordingly specify the samefinancial instrument in fields 506 and 516, respectively. For example,order 1 may be an electronic data transaction request to purchase(specified in field 508) a quantity (field 512) of a financialinstrument (field 506) at a value (field 510), and order 2 may be anelectronic data transaction request to relinquish (specified in field518) a quantity (field 522) of the same financial instrument (specifiedin field 516) at a value (field 520). The same financial instrument maybe associated with order book object 1. Thus, orders 1 and 2 both impactthe same order book object 540. Orders 1 and 2 are for different sidesof the same order book object and different values. In one embodiment,an electronic data multiple transaction request message may includeorders impacting the same side of the same order book object, but be fordifferent values/price levels. Order 3 may be an electronic datatransaction request to transact upon (transaction type specified infield 528) a quantity (field 532) of a financial instrument (field 526)at a value (field 530), where order book object 2 (data object 560) isassociated with the financial instrument specified in field 526.

The electronic data multiple transaction request message accordinglyallows a trader to specify multiple electronic data transaction requestsin the same electronic data multiple transaction request message (alllinked by mass order id, field 502), where the electronic datatransaction requests may be for different instruments or the sameinstrument, and may allow the trader to specify different values for thesame financial instrument, e.g., either on the same side (e.g., one ofbuy or sell) or a different side (e.g., the other of buy or sell).

In one embodiment, the multiple electronic data transaction requests inan electronic data multiple transaction request message may be sorted byvalue for each type. For example, an electronic data multipletransaction request message may be in a format that includes positionsthat may be identifiable by a position code. For example, in FIG. 5A,fields 504, 514 and 524 may be associated with first, second and thirdpositions, respectively, such that the optimization processor in anexchange computing system may read and process the first position first,the second position next, then the third position, and so on. Asdiscussed herein, the optimization processor may initially read orprocess a value in the first position, and may determine whether or notmessages in subsequent positions are processed by transaction integritymodules and/or transaction processing modules based on the results ofreading or processing the value in the first position. The electronicdata multiple transaction request message submitter's client computer,which is the computer that generates the electronic data multipletransaction request message, places the orders/values within thedifferent positions of an electronic data multiple transaction requestmessage. The electronic data multiple transaction request message'ssubmitter ensures that the electronic data multiple transaction requestmessage is properly formatted so as to be accepted and properlyprocessed by the optimization processor.

In one embodiment, the orders/transaction requests within an electronicdata multiple transaction request message are sorted by value for eachtransaction type from the electronic data transaction request associatedwith the best value to the electronic data transaction requestassociated with the worst value. For example, if an electronic datamultiple transaction request message includes multiple electronic datatransaction requests to relinquish the same financial instrument, thebest value for the relinquish transaction type for that financialinstrument in the electronic data multiple transaction request messageis the smallest value out of all of the multiple electronic datatransaction requests to relinquish the same financial instrument, andthe worst value for the relinquish transaction type for that financialinstrument in the electronic data multiple transaction request messageis the largest value out of all of the multiple electronic datatransaction requests to relinquish the same financial instrument. If anelectronic data multiple transaction request message includes multipleelectronic data transaction requests to acquire the same financialinstrument, the best value for the acquire transaction type for thatfinancial instrument in the electronic data multiple transaction requestmessage is the largest value out of all of the multiple electronic datatransaction requests to acquire the same financial instrument, and theworst value for the acquire transaction type for that financialinstrument in the electronic data multiple transaction request messageis the smallest value out of all of the multiple electronic datatransaction requests to acquire the same financial instrument.

In one embodiment, the electronic data multiple transaction requestmessage format may include all of the transaction requests fortransactions of one type (e.g., acquire) grouped together (e.g., inconsecutive positions in the electronic data multiple transactionrequest message) followed by all of the transaction requests fortransactions of another type (e.g., relinquish) grouped together (e.g.,in consecutive positions in the electronic data multiple transactionrequest message).

In one embodiment, the optimization processor may reject any electronicdata multiple transaction request message where all of the acquirevalues (e.g., values associated with electronic data transactionrequests requesting acquisition of a financial instrument) are not lessthan all of the relinquish values (e.g., values associated withelectronic data transaction requests requesting relinquishing of thefinancial instrument).

In one embodiment, the electronic data multiple transaction requestmessage may include a flag that indicates that the optimizationprocessor should sort the transaction requests within an electronic datamultiple transaction request message by type and value before theelectronic data multiple transaction request message is processed asdiscussed herein.

FIG. 5B illustrates another example electronic data multiple transactionrequest message 550. Electronic data multiple transaction requestmessage 550 may be similar to electronic data multiple transactionrequest message 500, and elements in FIGS. 5A and 5B that are similar toeach other may be referenced by the same reference numerals. Electronicdata multiple transaction request message 550 enables multiple orders tobe associated with the same financial instrument. Electronic datamultiple transaction request message 550 also enables multiple orders tobe associated with the same transaction type for the same financialinstrument. For example, orders 1, 2 and 4 are all associated withfinancial instrument 1. Thus, each order does not need to specify thefinancial instrument associated with that order. Electronic datamultiple transaction request message 550 accordingly reduces the numberof fields necessary to represent orders 1, 2 and 4. In particular,compared to electronic data multiple transaction request message 500illustrated in FIG. 5A, electronic data multiple transaction requestmessage 550 does not need to include data associated with field 516.Moreover, orders 1 and 4 are for the same transaction type (e.g., type1) for financial instrument 1. Thus, the same field, namely field 508,is used to specify the transaction type associated with both orders 1and 4, reducing the number of fields and/or the amount of data, thatwould be otherwise necessary to represent orders 1 and 4.

It should be appreciated that reducing the amount of data necessary torepresent orders, and thus the size of the messages transmitted to theexchange computing system, reduces the strain on the computers systemsand networks used to transmit such messages, reducing the overalllatency experienced by the transaction request submitters.

In one embodiment, implementing the electronic data multiple transactionrequest message reduces the amount and/or size of messages transmittedfrom client computers to the exchange computing system because multipleelectronic data transaction requests can be included in a singleelectronic data multiple transaction request message. For example, datathat is common to more than one electronic data transaction request(e.g., the transaction type associated with orders 1 and 4, as describedin connection with FIG. 5B) may only needed to be included once in theelectronic data multiple transaction request message, reducing the sizeof the data that is transmitted by a user's client computer to theexchange computing system, thus reducing the strain on computer systemsand networks that are used to communicate information between clientcomputers and the exchange computing system.

Optimization Processor

An exchange computing system, such as one implemented by the CME, mayinclude an optimization processor that determines whether some (e.g.,all but one) electronic data transaction requests in the same electronicdata multiple transaction request message are submitted to transactionintegrity modules and/or transaction processing modules.

The disclosed optimization processor may determine whether or not one ofthe incoming electronic data transaction requests (in particular, theelectronic data transaction request associated with the best value fromall of the electronic data transaction requests in the electronic datamultiple transaction request message) will cause the integrity logicprocessing (e.g., value banding and velocity logic) of the transactionintegrity modules to perform a corrective action. A corrective action,as discussed herein, by the transaction integrity modules may be toreject the transaction request that is checked by the transactionintegrity module. A corrective action may be to halt processing oftransaction requests for a predetermined amount of time. Based ondetermining how the best value will be processed by the transactionintegrity modules, e.g., whether the best value will be rejected by thetransaction integrity modules, the optimization module determineswhether other electronic data transaction requests in the sameelectronic data multiple transaction request message are submitted totransaction integrity modules, or are instead also rejected by theexchange computing system, without having to actually submit the otherelectronic data transaction requests in the same electronic datamultiple transaction request message to the transaction integritymodules. For example, the optimization processor may be in communicationwith a value banding module 152 and a velocity logic module 154 of anexchange computing system, which may collectively extract and analyze anelectronic data transaction request to determine whether the transactionrequest will cause a corrective action, such as a rejection of thetransaction request.

As discussed above, “better” than a reference value means lower than thereference value if the transaction is a purchase transaction, and higherthan the reference value if the transaction is a sell transaction. Saidanother way, for purchase transactions, lower values are better, and forrelinquish or sell transactions, higher values are better. As discussedabove, for example, if an electronic data multiple transaction requestmessage includes multiple electronic data transaction requests torelinquish the same financial instrument, the best value for therelinquish transaction type for that financial instrument in theelectronic data multiple transaction request message is the smallestvalue out of all of the multiple electronic data transaction requests torelinquish the same financial instrument. If an electronic data multipletransaction request message includes multiple electronic datatransaction requests to acquire the same financial instrument, the bestvalue for the acquire transaction type for that financial instrument inthe electronic data multiple transaction request message is the highestvalue out of all of the multiple electronic data transaction requests toacquire the same financial instrument.

The optimization processor may also additionally determine whether ornot one of the incoming electronic data transaction requests (inparticular, the electronic data transaction request associated with thebest value from all of the electronic data transaction requests in theelectronic data multiple transaction request message) would actuallytrade, or cause a match, e.g., with a resting order, and based on thatdetermination, may determine whether other electronic data transactionrequests in the same electronic data multiple transaction requestmessage are submitted to transaction processing modules. For example,the optimization processor may be in communication with a messagemanagement module 140, an order extraction module 146, and/or orderprocessing module 136 of an exchange computing system, which maycollectively extract and analyze an electronic data transaction requestand execute an instruction or action included therewith, includingdetermining whether the transaction request will cause or be involved ina match event.

Accordingly, if the optimization processor determines that the bestvalue for a transaction type in an electronic data multiple transactionrequest message will not pass the transaction integrity modules'integrity logic processing, or will not match with a previously receivedbut unsatisfied transaction request, the optimization processor avoidsfurther processing (such as by the transaction integrity modules or thetransaction processing modules) of the other transaction requests in thesame electronic data multiple transaction request message. The disclosedoptimization processor accordingly reduces, in many instances, theprocessing of the other (i.e., non-best) electronic data transactionrequests in an electronic data multiple transaction request messagebased on the results of processing the best electronic data transactionrequest for each transaction type via one or more of the transactionintegrity modules or the transaction processing modules.

Some of the processing, which may be avoided due to the implementationof the optimization processor, may include having to determine whether atransaction request fully trades (e.g., whether all of the requestedquantity of the order is satisfied/matches) or partially trades (e.g.,whether only some of the quantity is satisfied/matches and the remainingquantity rests on the book to await a subsequent suitable counterorder), and having to determine the trade prices (as opposed to thelimit or submitted price) at which quantities will match or trade.

For example, referring to FIG. 5A, the optimization processor may beable to determine whether Orders 2 and 3 (e.g., the non-best electronicdata transaction request values) are processed by computer intensivetransaction integrity modules and transaction processing modules basedon information related to Order 1 (e.g., the best electronic datatransaction request value, because it is in the first position in thesorted electronic data transaction requests), allowing the exchangecomputing system in many instances to minimize the overall processingperformed, conserving computing time and resources.

The disclosed optimization system may be implemented, in one embodiment,as an optimization module 600 as shown in FIG. 6A. FIG. 6A illustratesan example computing system 100 which includes optimization module 600,transaction integrity module 150, match engine module 106, and orderbook module 110. Optimization module 600 may include an optimizationprocessor. Exchange computing system 100 may be similar to, or the sameas, exchange computing system 100 described in connection with FIG. 1.Transaction integrity module 150 includes a value banding module 152 anda velocity logic module 154, each of which protects the integrity of theexchange computing system 100 by performing a corrective action (e.g.,rejecting the transaction request, or halting a matching processor) ifundesirable conditions are detected. Match engine module 106 and orderbook module 110 are utilized to attempt to match an incoming transactionrequest, and place any unsatisfied transaction request quantity on theorder book object for the associated financial instrument.

As shown in FIG. 6A, client computer 602 transmits electronic datamultiple transaction request message 500 to exchange computing system100. Electronic data multiple transaction request message 500 includeselectronic data transaction requests 504, 514 and 524.

Electronic data transaction requests 504, 514 and 524 may be requestsassociated with the same transaction type, e.g., acquire or relinquish,for the same financial instrument. Electronic data multiple transactionrequest message 500 and its contents are generated by a user associatedwith client computer 602. Electronic data transaction requests 504, 514and 524 may be positioned and arranged within the electronic datamultiple transaction request message 500 in a sequence such that theelectronic data transaction request with the best value, as discussedherein, is located in a position known to the exchange computingsystem/optimization module 600 to be the position for the best value.Thus, the optimization module can identify the transaction request withthe best value for any given transaction type in one electronic datamultiple transaction request message.

As shown in FIG. 6B, optimization module 600 receives electronic datamultiple transaction request electronic data multiple transactionrequest message 500. In one embodiment, optimization module 600 maycheck whether the electronic data transaction requests within electronicdata multiple transaction request message 500 are sorted from best toworst value, as described above. In one embodiment, optimization module600 identifies a first position within electronic data multipletransaction request message 500 which indicates that the value in thefirst position should be understood by the optimization module to be thebest value.

As shown in FIG. 6C, the optimization module 600 may be in communicationwith transaction integrity module 150. The optimization module 600 maytransmit the best value, the value associated with electronic datatransaction request 504 in example FIG. 6C, to the transaction integritymodule 150.

If the transaction integrity module 150 determines that electronic datatransaction request 504 does not pass the integrity logic processing oftransaction integrity module 150, i.e., would be rejected by thetransaction integrity modules, optimization module 600 may reject theentirety of electronic data multiple transaction request message 500,and additionally transmit a notification to client computer 602 thatelectronic data multiple transaction request message 500 has beenrejected for transaction integrity module failure, as shown in FIG. 6D.It should be appreciated that due to the implementation of optimizationmodule 600, the exchange computing system 100 is able to reject all ofthe electronic data transaction requests in electronic data multipletransaction request message 500 by only transmitting and checkingelectronic data transaction request 504 via the transaction integritymodule 150. Said another way, optimization module 600 is able toconclude that electronic data transaction requests 514 and 524 will notpass the transaction integrity module 150's logic without actuallyhaving to transmit electronic data transaction requests 514 and 524 tothe transaction integrity module 150. The transaction integrity module150 accordingly only needs to process (e.g., check) electronic datatransaction request 504, eliminating the consumption of computingresources and time/processing delay that would otherwise be necessary toadditionally process electronic data transaction requests 514 and 524.

If electronic data transaction request 504 passes transaction integritymodule 150's integrity logic processing, then the optimization module600 may route some or all of the other transaction requests for the sametransaction type, e.g., transaction request 514 and 524, through thetransaction integrity modules. If any of the subsequent transactionrequests fails the transaction integrity module's integrity logicprocessing, the optimization module may be able to reject all othertransaction requests of the same transaction type that are worse thanthe failed subsequent transaction request. Thus, for example, ifelectronic data transaction request 504 passes transaction integritymodule 150's integrity logic processing, then transaction request 514 isrouted to transaction integrity modules 150. If transaction request 514fails the transaction integrity module 150's integrity logic processing,then the optimization module rejects both transaction request 514 and516. Accordingly, in this example, the optimization module is able toreject transaction request 516 without needing transaction integritymodules to actually test or check transaction request 516, reducing theamount of processing performed by the exchange computing system 100.

Referring now to FIG. 6E, the optimization module may transmit the bestvalue, electronic data transaction request 504, to the match enginemodule 106. Match engine module 106, or the optimization module 600 incommunication with match engine module 106, may determine whetherelectronic data transaction request 504 will match with a resting order,e.g., previously received but unsatisfied transaction request that iscounter to the transaction type of transaction request 504.

If the optimization module 600, in communication with match enginemodule 106, determines that transaction request 504 will not match anyof the currently resting orders in the order book object associated withthe financial instrument associated with transaction requests 504, 514and 524, optimization module 600 transmits transaction requests 514 and524 directly to the order book module 110, as shown in FIG. 6F. Itshould accordingly be appreciated that due to the implementation ofoptimization module 600 in example FIGS. 6E and 6F, the match enginemodule 106 avoids the need to process or attempt to match transactionrequests 514 and 524.

If the optimization module 600, in communication with match enginemodule 106 and order book module 110, determines that transactionrequest 504 will match a currently resting order in the order bookobject associated with the financial instrument associated withtransaction requests 504, 514 and 524, optimization module 600 may routesome or all of the other transaction requests for the same transactiontype, e.g., transaction request 514 and 524, through the match enginemodule 106. If any of the subsequent transaction requests does not match(e.g., based on the match engine module logic), the optimization modulemay be able to directly transmit all other transaction requests of thesame transaction type that are worse than the un-matched subsequenttransaction request directly to the order book module 110 so that thetransaction requests may be added as resting orders to the order bookobject. Thus, for example, if electronic data transaction request 504matches a currently resting order, then transaction request 514 isrouted to the match engine module 106. If transaction request 514 doesnot match based on the match engine module 106's logic, thenoptimization module routes transaction request 516 directly to the orderbook module 110. Accordingly, in this example, the optimization moduleis able to route transaction request 516 to order book module 110without needing match engine module 106 to attempt to match transactionrequest 516, reducing the amount of processing performed by the exchangecomputing system 100.

FIG. 7 illustrates an example computer implemented method 700 which maybe implemented in an exchange computing system that includes theoptimization processor described herein. Embodiments may involve all,more or fewer actions indicated by the actions of FIG. 7. The actionsmay be performed in the order or sequence shown or in a differentsequence.

In step 702, an optimization processor (which may be, or be located in,the optimization module 600 discussed above) in the exchange computingsystem may receive an electronic data multiple transaction requestmessage, which includes multiple orders (e.g., electronic datatransaction requests) at different prices or values for a same financialinstrument. The optimization processor then determines whether theinstructions or transaction requests in the electronic data multipletransaction request message are grouped by side, for example, bytransaction type, and sorted beginning with the best value or price, asshown in step 704. The optimization processor rejects the electronicdata multiple transaction request message if the electronic datatransaction requests are not grouped by transaction type and are notsorted beginning with the best price, as shown in step 706.

In step 708, the optimization processor determines whether all of thebuy prices are less than all of the ask prices and, if not, rejects theelectronic data multiple transaction request message as shown in step706. The check in step 708 may be performed to ensure that electronicdata transaction requests within the electronic data multipletransaction request message do not self-match, e.g., electronic datatransaction requests to acquire a data object do not match withelectronic data transaction requests in the same electronic datamultiple transaction request message to relinquish the data object(e.g., submitted by the same client computer, because they are in thesame electronic data multiple transaction request message).

In one embodiment, the optimization processor may determine whether allof the values associated with acquire electronic data transactionrequests are less than all of the values associated with relinquishelectronic data transaction requests, and whether the electronic datatransaction request associated with the best value for acquiring thedata object is greater than a lead acquisition value stored in an orderbook object for the data object. Upon determining that all of the valuesassociated with acquire electronic data transaction requests are lessthan all of the values associated with relinquish electronic datatransaction requests, and that the electronic data transaction requestassociated with the best value for acquiring the data object is greaterthan a lead acquisition value stored in an order book object for thedata object, the optimization processor may store data associated withthe relinquish electronic data transaction requests in the order bookobject associated with the data object. Thus, the optimization processormay determine whether the highest bid is now at or above the previousbest bid on the book, and if so, the optimization processor can forwardall of the sell orders in the electronic data multiple transactionrequest message without having to check whether the sell orders matchagainst any of the resting bid orders, thus minimizing the amount ofprocessing performed, or needing to be performed, by the match enginemodule.

In step 710, the optimization processor determines if the best price foreach transaction type passes the integrity checks performed by thetransaction integrity module and, if not, the optimization processorrejects the electronic data multiple transaction request message, againleading to step 706.

The optimization processor may also determine whether the best pricematches against a resting order and, if not, the optimization processorbypasses match attempts for all other values in the electronic datamultiple transaction request message, and adds all of the other ordersto the order book for that financial instrument, as shown in step 714.If the best price matches against a previously resting order, theoptimization processor, in connection with the match engine module andthe order book module, continues checking whether the next best pricematches against a resting order. Upon encountering or processing a valuein the sorted sequence that does not match against a resting order, theoptimization processor adds all such remaining orders to the order book,thus bypassing having to process all remaining orders for that same sidethrough the match engine module.

FIG. 8 illustrates an example computer implemented method 800 foroptimizing processing of electronic data multiple transaction requestmessages. Embodiments may involve all, more or fewer actions indicatedby the actions of FIG. 8. The actions may be performed in the order orsequence shown or in a different sequence.

In one embodiment, method 800 may be implemented in a data transactionprocessing system in which data objects are transacted by a hardwarematching processor that matches electronic data transaction requests forthe same one of the data objects based on multiple transactionparameters received from different client computers over a datacommunication network.

At step 802, method 800 includes receiving an electronic data multipletransaction request message including a plurality of electronic datatransaction requests. Each of the electronic data transaction requestsmay request performance of a same type of transaction for a quantity ofthe same data object at a value. The electronic data transactionrequests may be sorted, within the electronic data multiple transactionrequest message, by value for each transaction type, from the electronicdata transaction request associated with the best value to theelectronic data transaction request associated with the worst value.

At step 804, method 800 includes determining whether the electronic datatransaction request associated with the best value will be rejected by atransaction integrity module of the data transaction processing system.

At step 806, method 800 includes, upon determining that the electronicdata transaction request associated with the best value will be rejectedby the transaction integrity module, rejecting the plurality ofelectronic data transaction requests.

Atomic Dual-Pass Processing

In one embodiment, the electronic data multiple transaction requestmessage may include an atomic instruction indicating that the multipleelectronic data transaction requests should only be processed if all ofthe multiple electronic data transaction requests can match againstpreviously received but resting electronic data transaction requests. Inother words, if any of the multiple electronic data transaction requestscannot be matched based on the current state of the order book objectsassociated with the financial instruments listed in the electronic datamultiple transaction request message, the optimizationprocessor/exchange computing system does not process or attempt to matchany of the multiple electronic data transaction requests.

In one embodiment, the optimization processor may associate a flag witheach transaction request, and upon evaluating an electronic datatransaction request, set the flag to indicate whether the transactionrequest, if processed, will result in a match. The optimizationprocessor traverses through all of the multiple electronic datatransaction requests, e.g., in a first pass, setting the flag to Yes orNo, or alternatively, On or Off, for each transaction request, dependingupon whether the transaction request will be matched. The optimizationprocessor then determines whether all of the flags associated with themultiple electronic data transaction requests in an electronic datamultiple transaction request message are set to be Yes, or On,indicating that each electronic data transaction request will bematched. The optimization processor then processes/actually matches,e.g., in a second pass through the transaction requests, each of theelectronic data transaction requests in sequence. The disclosedembodiments accordingly enable a user to submit messages that areprocessed either as an atomic group, or not at all.

As discussed herein, an order to trade, or trade order, is effectivelyan order or request for a transaction with respect to a financialinstrument, such as a futures contract, options on future, spread orother combination contract, etc., wherein the transaction furtherspecifies at least whether the trader desires to buy (bid) or sell(offer) the financial instrument, the desired price therefore, andquantity thereof. It should be appreciated that other factors, such asconditions, e.g. stop orders, etc., may also be specified. Further theprice may be specified as a fixed value, relative value, upper or lowerlimit value, or range of values. The financial instrument may compriseone or more component instruments or component transactions. A financialinstrument comprising more than one component instrument may also bereferred to as a combination contract or combination financialinstrument. A combination contract, also referred to as a strategy, maybe defined as a combination of orders for outright contracts where eachorder for an outright contract forms a “leg” of the strategy, alsoreferred to as a leg order. The definition of the combination contractfurther specifies whether buying a unit quantity of the strategy, i.e.the combination contract, requires a given leg to be bought or sold andin what quantity. Strategies may be defined by the exchange andadvertised to traders as tradable instruments and/or they may be definedupon request by a market participant, such as via a request submitted tothe exchange computing system. As described above, a combinationcontract permits the simultaneous trading of the component instrumentsthereof, i.e. simultaneous submission on the orders therefore, into amarket for that instrument. Combination contracts may be used to hedgerisk, e.g. risk that a price of the underlier will rise or fall in thefuture, risk that prices will be volatile, risk of a rise or fall ininterest rates, or other risk. It will be appreciated that marketparticipants may attempt to simulate combination contracts, particularlythose not defined by the exchange computing system and therefore were nospecific market for the combination contract exists, by separatelysubmitting the component transactions as separate orders into theassociated markets but may incur additional transaction fees and therisk, referred to as “leg risk,” that the individual orders may be notbe processed as desired, such as due to a change in the market at thetime of submission or proximate thereto.

An order for a financial instrument comprising more than one componentinstrument, i.e. a combination financial instrument or contract, enablesa trader to transact in multiple instruments with a single transactionwhich, for example, reduces transaction fees and/or the delay betweensubmission of orders for the involved financial instruments (which maybe advantageous when prices for those instruments are quickly changing),thereby reducing leg risk. In one embodiment, the dual-pass processingby an optimization processor may be implemented to reduce or eliminateleg risk. In particular, the client computer may use the disclosedelectronic data multiple transaction request message to specifyelectronic data transaction requests that are either all executedimmediately (e.g., during the second pass of the dual-pass optimizationprocess) or not executed at all, and deleted immediately without beingstored in the respective order book objects.

The atomic dual-pass optimization described herein may also allow afirst user to submit multiple transactions that are processedatomically, e.g., without the risk of intervening transactions fromother users being executed between the first user's multiple electronicdata transaction requests.

The atomic dual-pass functionality of the optimization processor enablesthe exchange computing system to guarantee that the multipleinstructions linked by the mass order identifier are executed as a unit,e.g., atomically. In one embodiment, an electronic data multipletransaction request message including the atomic dual-pass instructionis only executed (e.g., matched) if all instructions within the ordercan be executed immediately. Otherwise, the electronic data multipletransaction request message and its multiple electronic data transactionrequests are cancelled.

In one embodiment, an electronic data multiple transaction requestmessage may allow the exchange computing system to receive a set ofrelated transaction requests (for different data objects) from a firstsender of the plurality of senders and test the set to determine if allthe transaction requests can be executed based on the current state ofthe order book objects associated with the different data objects. Ifall the transaction requests cannot be executed, all the transactionrequests are rejected. If all the transaction requests can be executed,all the transaction requests are executed before executing any othertransaction request for any of the data objects received subsequent tothe set of related transaction requests and before communicating aresult of the execution of any of the set of related transactionrequests. In one embodiment, executing the set of related transactionrequests may comprise optimizing the executing as discussed herein,e.g., via an optimization processor.

Transaction Integrity Modules

Transaction integrity modules may be implemented to automaticallyperform a corrective action, e.g., halt or release the matchingprocessor depending on the state of the system and/or the contents ofthe electronic data transaction request messages. For example, upondetecting an undesirable condition within the data transactionprocessing system, transaction integrity modules may cause halting ofthe matching processor, which prevents the matching processor frommatching messages, e.g., places the system or data objects related tothe undesirable condition in a reserved state. After the passage oftime, receipt of a number of messages, or some other predeterminedcondition, transaction integrity modules may release the matchingprocessor, or allow the matching processor to resume matching messages.

Transaction integrity modules may also check certain messages or ordersfor products traded via the exchange computing system. Transactionintegrity modules may also check certain messages or orders for orderbooks maintained on the exchange computing system. The products or orderbooks may be represented as data objects within the exchange computingsystem. The checked messages may be recently received messages (e.g., alimit price on a new incoming order, or a modification of a previousorder), or recently triggered messages (e.g., a limit price in a stoporder resting on the books that is triggered by a trade at the stopprice).

Transaction integrity module processing is time consuming and increaseslatency, in part because it compares each transaction request value topredetermined and/or dynamic thresholds. Applicants have determined thatif the best transaction request value from a plurality of electronicdata transaction requests for the same transaction type of the samefinancial instrument fails the integrity logic testing of thetransaction integrity module, then all of the other transaction requestsin the same electronic data multiple transaction request message for thesame transaction type would also fail the integrity logic testing of thetransaction integrity module. Thus, the optimization processor onlyneeds to test the best value in a group of transaction requests for thesame side (e.g., transaction type) of a financial instrument in caseswhere the best value fails the integrity logic testing, and in suchcases, can reject all of the other transaction requests for the sametransaction type without having to test all of the other transactionrequest values.

Referring back to FIGS. 6A through 6F, if the optimization moduledetermines that a transaction request should be routed to thetransaction integrity module 150, the transaction request may be subjectto the processing of a value banding module 152 and/or a velocity logicmodule 154.

The value banding module 152, in one embodiment, prevents erroneousorder entry prices. For each product, a range, or “band”, of validvalues is configured. If an order is entered for a product with a pricefalling outside of the price band, the value banding module 152 willreject the transaction request, so that the transaction request is notmatched or added to the order book. In other words, a transactionrequest is not further processed or analyzed if the value banding module152 rejects the transaction request. Thus, in one embodiment, the valuebanding module 152 may be useful to prevent antagonistic or erroneousorders, such as limit bids at values well above the market or limitoffers.

In one embodiment, the value banding module 152 rejects any buytransactions above a “reference last value” plus a fixed band value, andrejects any sell transactions below a “reference last value” minus afixed band value. The reference last value may be determined by the mostrecent transaction, or the best bid or best offer through the mostrecent transaction. The reference last value may also be determined by asettlement value, or an exchange determined value, only if no values areavailable from the most recent transaction or the best bid or best offerthrough the most recent transaction.

Thus, the value banding module 152 may reject electronic datatransaction requests having values outside of a banding thresholddefining an allowable value range.

If a transaction request is not rejected by the value banding module152, the transaction request is routed towards a velocity logic module154, which implements velocity logic processing.

The values to which velocity logic processing is applied (whether theybe the current sampled, derived or measured parameters or value at whichdifferent quantities will actually trade, depending on whether the ordermatches at all, and if so, whether it matches partially or fully) arecompared with one or more sampled, derived, measured or computed values,or ranges thereof, representative of each interval or slice of timepreceding the current sample, the collection of which may be referred toas a window as well as, in one embodiment, with some or all of theprevious values sampled, derived or measured within the currentinterval.

FIGS. 9A and 9B illustrate various diagrams depicting how samples may beobtained and compared for transaction integrity processing. Transactionintegrity modules sample or otherwise derive a market value parameter(P_(n)), which may be a high (V_(hi)) and/or low (V_(lo)) value thereof,during time intervals or slices in that elapse upon a duration of time.For example, FIG. 9A illustrates time intervals in associated withparameters P_(n) which are representative of the value of a data objectover the duration of the interval, e.g. the highest and/or lowest valueover the interval.

During each interval or time slice, the sampled market parameter value,e.g., of each incoming trade or triggered limit value from a conditionalorder, is compared with one or more parameters indicative of the marketvalue determined during each of a defined number of preceding intervalsdescribed above. In one embodiment, the sampled market parameter value,e.g., of each incoming trade or triggered limit value from a conditionalorder, is alternatively or additionally compared with one or moreparameters sampled, derived or measured during the current interval.

It should be appreciated that sampled market parameter values oftriggered limit values from conditional orders determined during a giveninterval refers to limit values that are triggered during the giveninterval.

In one embodiment, the sampled or derived parameter obtained during thecurrent interval may be compared with comparative parameters/values,such as the values of the previously acquired samples of the precedingintervals, as well as the preceding values acquired during the currentinterval. In an alternative embodiment, at each interval othercomparative parameters are determined, such as the highest and lowestvalue of the monitored parameter over the duration of particularinterval, to which the sampled parameter obtained during the currentinterval is compared.

For the current interval, such highest and lowest values are determinedas each market parameter is sampled, measured or derived, for comparisonwith the most current (e.g., incoming during the current interval orlimit value from a conditional order triggered during the currentinterval) market parameter value.

Initially, when a trading period commences or otherwise there is nomarket history, e.g. the market opens, or otherwise when operation oftransaction integrity modules is initiated (or after a sufficient periodof market inactivity as will be discussed below), the first sample ofthe market value parameter (P₁) may be defined, such as statically, orotherwise derived, such as based on the parameter value at the close ofthe prior trading period, the first value sampled, derived or measuredupon commencement of the trading period, or based on some other methodsuch as derivation of an indicative opening price.

The number of preceding intervals/slices which are subject to comparisonis configurable and effectively defines a rolling window of time whereolder intervals are discarded as time moves forward, e.g. new intervalscommence. In one implementation, this rolling time window may bestructured or otherwise conceptualized as multiple overlappingsampling/monitoring windows or threads, referred to as overlapping timebuckets (be) illustrated in FIG. 9B, which run for a defined period oftime and where a new time bucket is commenced, the market valueparameter is sampled or otherwise determined or derived, upon eachelapse of the interval time i, and time buckets commenced at a timeolder than the defined number of preceding intervals are discarded. Thenumber of active time buckets, the duration thereof, and the interval atwhich buckets are started then defines the window of time over which, orotherwise how far back, transaction integrity modules operate. In oneembodiment, if there has been no market activity during any of theintervals within the time window, the disclosed system considers thenext market event to be akin to the start of a new trading period asdescribed above.

It will be appreciated that whether transaction integrity modules areconceptualized as overlapping time buckets or as a duration of timedefined by intervals or slices, as described, or in any other manner,may be implementation dependent and all such conceptualizations, now orlater developed, are contemplated herein.

In one embodiment, the time window over which an incoming order iscompared may be defined order by order, e.g. based on the incomingorder. That is, each incoming order has its own time window wherein theincoming order is compared with values within its associated timewindow. For example, each incoming order may be compared with ordersreceived in the window and preceding the current order. As describedelsewhere, the window may be specified as an amount of time or a numberof intervals.

Each sampled, derived or measured value obtained during the current timeinterval or slice is compared with one or more comparative valuesdetermined for preceding time intervals/slices, referred to as the timewindow, as well as, in one embodiment, each preceding sampled, derivedor measured value, or the highest and or lowest thereof, during thecurrent interval.

If the sampled value deviates, i.e. is above or below, from any of thecomparative values by a threshold amount, which may be configurable andmay be zero, transaction integrity modules may indicate a qualifyingevent and indicate that action should be taken. In one implementation,the threshold amount is not less than one. The threshold amount may bestatically or dynamically configured and reflects the magnitude ofmarket movement between compared values that may be tolerated, i.e. thethreshold amount delineates magnitude of movement/change, up or down,considered to be normal for the market and avoids, for example, placinga market in a reserved state that is not, in fact, under duress.

The threshold amount may be based on the product being traded orassociated order book and may be, for example, a number determined bythe GCC. For example, the threshold amount may be a multiple of anon-reviewable range (“NRR”) that is pre-determined by, e.g., anadministrator of the exchange computing system. A NRR may define a rangethat is considered a reasonable trading deviation from a product's fairor active (e.g., currently observed) value. In one embodiment, the NRRmay be a range that an administrator or administrators of the exchangecomputing system consider to be a reasonable amount for a product totrade away from the product's fair value. In one embodiment, the NRR maybe reviewed and established on a periodic basis, e.g., quarterly. Theexchange administrators may consider a variety of metrics, such asvolatility, average daily ranges, margin, and tick value, for example,to determine the NRR.

FIG. 10 illustrates an example comparison plot 1000 of parameters thatare sampled according to an example transaction integrity module,namely, a velocity detection and mitigation system. In FIG. 10, sampledparameters obtained during the interval i₄, namely, P₅, are comparedwith each of the preceding values sampled in interval i₄ as well as thevalues P₄, P₃, P₂ and P₁, or the high (V_(hi)) or low (V_(lo)) valuesthereof, of the preceding intervals. Plot 1000 may effectively be usedto measure the steepness and direction of the slope between the marketvalue at the current interval and each of the preceding intervals wherea qualifying event may be determined when the steepness of the slope, orangle or other value representative thereof, whether positive ornegative, exceeds, or otherwise deviates from, a defined threshold valueindicative, for example, of an extreme market movement. The slope may bemay be positive as illustrated in FIG. 10, or negative, betweenintervals.

In one embodiment, rapid oscillation or thrashing of the market valuewithin the threshold values may also be detected and may also signifythat the market is not operating properly, triggering the remediesdescribed herein.

In one embodiment, the interval width, referred to below also as theduration of time or time slice length, may be dynamic and may varyinterval to interval such as based on market activity, e.g. volume orvolatility. For example, an interval may be defined as every 10milliseconds, or after 10 orders have been received. As the comparativevalues computed at each interval are representative of the activityduring that interval, the amount of activity aggregated together in oneinterval may thereby be normalized. In the case of dynamic intervalwidths, the time window over which values are compared, as describedherein, may be specified in terms of an amount of time, rather than anumber of intervals, so that the window may be a constant size eventhough the interval size may vary.

Referring back to FIGS. 6A to 6F, integrity logic may be performed bythe transaction integrity module that determines whether an electronicdata transaction request message will cause or be involved in a match,and if so, whether some but not all (e.g., a partial match), or all(e.g., a full match) of the quantity associated with the electronic datatransaction request message is matched. A transaction integrity modulemay also assign message values or match values as comparison values. Inother words, a transaction integrity module may determine how much, ifany, quantity of an electronic data transaction request message willmatch and at what value, and then assign the message value and/or anymatch values as comparison values to be checked, depending on whether amatch is detected at all, and if so, how much quantity associated withthe electronic data transaction request message will match.

Transaction integrity modules may identify at least one comparativevalue of the product, which may be stored, such as in a memory, e.g.,memory 204, for example in association with the data representative of atime window, for later comparison with future identified comparisonvalues upon each elapse of the duration of time, e.g. each interval inas shown in FIGS. 9A and 9B, and determining each previously identifiedcomparative value identified within a threshold time thereof. Asdescribed above, during each the elapse of the time, each comparisonvalue may further be compared with comparative values comprising thepreceding comparison values, or a derivation thereof, determined duringthe elapse of time. As described herein, the comparative value may bederived from the same or a different parameter from the comparison valueand more than one comparative value may be determined, such as a minimumand maximum thereof. Upon initiation of monitoring, such as when themarket opens or re-opens or trading otherwise commences or after asufficient period of inactivity (such as within the threshold time), theinitial comparison and comparative values may be initialized toconfigured values or otherwise defined according to rules such as beingbased on the state of the market at the close of the prior tradingperiod, e.g. based on an indicative opening price.

In one embodiment, a comparative value may be updated or revised basedon previous object values. When applied to an electronic trading system,a comparative value may be a pre-defined threshold that is updated uponeach elapse of duration of time based on a product's values during oneor more previous elapses of durations of time.

In one embodiment for use in markets for which outright orders (ordersactually placed by a trader) as well as implied orders (orders generatedby the Exchange based on outright orders placed in other markets, e.g.spread orders), may be received, only aggressor orders, i.e. outrightorders, may be included in the derivation of the comparative values andfurther utilized as comparison values. In this embodiment, receivedimplied orders may be ignored by the exchange computing system.

In one embodiment, the value of the product comprises, for example, abid price of the product, an ask price of the product, a last tradedprice of the product, a last traded quantity of the product, avolatility of the product, or other market attribute value, orcombination thereof. It will be appreciated that the value of theproduct may be determined according to other metrics of product value.

In one embodiment, a transaction integrity module determines thecomparison value of the product as a value of each order to trade theproduct received during the elapse of the duration of time, e.g. the bidprice, the ask price or trade price. In one embodiment, the comparativevalue is derived from the same parameter as the comparison value. Itwill be appreciated that fewer than all orders to trade may be compared,and that this sampling frequency may be configurable.

Alternatively, the transaction integrity module may determine the atleast one comparative value of the product as a minimum value of theproduct over the duration of time, e.g. the interval in which justelapsed, maximum value of the product over the duration of time, anaverage of the value of the product over the duration of time, orcombinations thereof. In one embodiment, the comparative value(s) may becomputed as a weighted average wherein more recent values are favoredover older vales.

The threshold time, which in one implementation may be the Time SliceCount, defines how far back the transaction integrity module will look,referred to above as a “window” or number of active slices or intervals,i.e. how many intervals will be compared, and may be specified inseconds, milliseconds and/or as a multiple of the duration of time, i.e.interval in, e.g. Time Slice Count. It will be appreciated thatdifferent threshold times, e.g. asymmetric time windows, may bespecified for positive market changes and negative market changes, suchas where the rate of negative movement, e.g. a dip, is determined to bemore critical than the rate of positive market movement, e.g. a spike.It will be appreciated that the threshold time may be set so as not tobe less than a minimum amount of time required for a market participantto react to a change in the market, e.g. receive and assimilate marketdata indicative of the change and submit an order responsive thereto. Inother words, the threshold time should be set so as to allow the marketparticipants a chance to respond and correct an extreme market changebefore the system transaction integrity module reacts thereto asdescribed.

The transaction integrity module may determine a difference between theidentified comparison value, e.g. sample, and each of the determinedpreviously identified comparative values. The current sample/comparisonvalue is compared only with previously identified comparative valuesthat are within the defined time window, i.e. within the threshold timeof the current time.

The transaction integrity module may determine if any of the determineddifferences deviate, either higher or lower, from a threshold value. Asdescribed above the threshold value defines the magnitude of movement,either up (positive) or down (negative), which would be tolerated, e.g.considered normal market behavior. The threshold value may be specifiedin terms compatible with the values being monitored and compared, suchas price ticks, points or other metric. For example, the threshold valuemay be 10 ticks. If the comparison value differs from an of the relevantprior comparative values but more than 10 ticks, either more than 10ticks above or more than 10 ticks below, a deviation is determined. Itwill be appreciated that the threshold values may be asymmetric, i.e. athreshold value may be specified for positive market changes and adifferent threshold value may be specified for negative market changes,such as where market dips are considered more critical than marketspikes. In one embodiment, the threshold value(s) may be dynamic and mayvary over time, such as from interval to interval, such as based onmarket activity, e.g. volume or volatility.

It will be appreciated that the comparative values and/or the thresholdvalues may be configured such that a comparison subsequent to the elapseof the duration of time may not cause a result different from than hadthe comparison been performed just prior to the elapse of the durationof time. For example, it may be desirable to configure the comparativeand/or threshold values such that an incoming order received after theend of an interval would cause the same result as if that order had beenreceived just prior to the end of that interval.

The transaction integrity module may perform an action when any of thedetermined differences deviate the threshold value. That is, if themarket moved too far, up or down, too fast, e.g. the slope or gradientof the movement (or angular or other measure thereof) versus the timeover which the movement is measured is too steep, positive or negative,it is determined that a qualifying event has occurred, referred to as a“Velocity Logic Event,” and one or more actions may be take or caused tobe taken.

In one embodiment, the action may include placement of the market forthe product in a reserved state, as was described above, such as for alimited time period which may be configurable and may be a static ordynamic value and may vary among markets. In one embodiment, if duringthe reserved state additional conditions, such as based on whether themarket is recovering to a normal operating state or not as the reservedstate is nearing an end, are met, the time limit for staying in reservedstate may be extended. Alternatively, or in addition thereto, the actionmay include transmission of an alert to an operator of the exchange,such as the GCC of the CME, a trader of the product, or a combinationthereof. Alerts may be sent as market data. Where the market is placedin a reserved state, the alert may further advise the recipient of thisstate. A subsequent message may then be sent when the market is takenout of the reserved state or if the reserved state is extended.Alternatively, or in addition thereto, the action may include permanentor temporary enablement of trading opportunities for the product in adifferent market. For example, implied markets for which the currentproduct may be a leg, etc. may be enabled to create additional matchingopportunities, i.e. additional liquidity. Alternatively, or in additionthereto, the action may include permanent or temporary prevention oftrading of the product at a price outside of a price limit, i.e. aceiling or floor. If the detected extreme movement is downward, thelimit may set as a limit below which trading is not allowed, e.g. afloor. Alternatively, if the detected extreme movement of the market isupward, the limit may be set as a limit above which trading is notallowed, e.g. a ceiling. In one embodiment, if orders to trade aresubsequently received substantially close to, or at, or otherwise withina threshold of, the limit, the limit may be periodically raised (orlowered), such as after a defined delay period, to gradually allow amarket, intent on reaching a particular price, to eventually reach theprice in a controlled manner, e.g. the market is slowed down.

Alternatively, or in addition thereto, the action may include modifyingthe matching/allocation algorithm used to allocate incoming orders toresting orders. For example, if the current matching algorithm isFirst-In-First-Out (“FIFO”), also referred to as Price-Time, thealgorithm may be changed to Pro-Rata. Other algorithms which may be usedinclude Price Explicit Time, Order Level Pro Rata, Order Level PriorityPro Rata, Preference Price Explicit Time, Preference Order Level ProRata, Preference Order Level Priority Pro Rata, Threshold Pro-Rata,Priority Threshold Pro-Rata, Preference Threshold Pro-Rata, PriorityPreference Threshold Pro-Rata, Split Price-Time Pro-Rata. See, forexample, U.S. patent application Ser. No. 13/534,399 entitled “MultipleTrade Matching Algorithms” herein incorporated by reference in itsentirety and relied upon.

In one embodiment, the transaction integrity module may receive theduration of time, the threshold time and the threshold value, or otherparameters which control the operation of the transaction integritymodules, such as from the operator of the exchange computer system, e.g.the GCC of CME. These configurable parameters include: which markets tobe monitored if not all markets, such as where performance constraintslimit deployment or where it may be determined that some markets are notsusceptible to the problems described herein and therefore need not bemonitored; the comparison value (which may be referred to below as theVL Price or Trade Price), such as which parameter of the market shouldbe used during the operation of the transaction integrity module and/orthe initial value thereof, which may be specified as a dollar amount,tick value or other metric; the comparative values (which may bereferred to below as the VL Ref Low and VL Ref High values), such aswhich parameter(s) of the market should be used during the operation ofthe transaction integrity module and/or the initial value(s) thereof,which may be specified as a dollar amount, tick value or other metric;the duration of time or interval (which may be referred to below as theTime Slice Length) and may be specified as a number of seconds ormilliseconds; the threshold time or window (which may be referred tobelow as the Time Slice Count or number of intervals or alternatively asthe Time Slice Count*Time Slice Length) and may be specified as a numberof intervals or a length of time, in seconds or milliseconds forexample, and may be a multiple of the duration of time/interval/TimeSlice Length; the threshold value (which may be referred to below as theVL Value); the action(s) to be taken; the time limit for keeping amarket in a reserved state; or other parameters. It will be appreciatedthat any or all of these parameters may be statically defined forapplication to all markets, may vary from market to market and/or may bedynamically configured/re-configured during operation, eitherautomatically responsive to market conditions or manually, e.g. by theoperator of the exchange computer system 100.

FIG. 11 illustrates an example plot showing an incoming message value 93that falls outside of defined threshold range after performing therequisite comparisons and accordingly raises, e.g., an action such asplacing the market for the product in a reserved state.

The exchange computing system is typically configured to processincoming messages as discussed herein with reference to FIG. 1. However,if the exchange computing system receives an order or message to tradeproduct at a value or price that violates the conditions defined herein,transaction integrity modules may take, or otherwise cause, a differentaction. This action may include alerting the operator of the electronictrading system or exchange, such as the GCC of the CME, placing themarket in a reserved state whereby orders may be received and pricediscovery may occur but matching of trades is otherwise suspended, orinstitute one or more temporary or permanent limits, such as pricelimits, e.g. a maximum price and/or minimum price, wherein only tradesat prices within the limit(s) are allowed, or combinations thereof. Inan alternate embodiment, other actions may include enabling additionalliquidity, i.e. trading opportunities, for the particular product, suchas by temporarily or permanently enabling implied opportunities whereby,for example, additional liquidity may be found in markets forcombination products, e.g. spreads, involving the particular product.

With respect to placing the market in a reserved or paused state, whilean instrument may not trade when it is reserved, price discovery maystill occur, e.g. an indicative opening price of that instrument may bederived and disseminated to the market. The indicative opening price mayreflect the price the instrument would be trading at if the market wereopen. Placing an instrument in a reserved state allows marketparticipants to enter additional orders that adjust the indicativeopening price to a level that reflects buyers competing with otherbuyers and sellers vying against other sellers. The present embodimentsmay temporarily suspend trading until the market is adjusted within athreshold range, or when a period of time lapses. The period of time mayvary in length in relation to the time of day, the product traded,market volatility and/or any other relevant market condition orcombination of market conditions. Similarly, the threshold range mayvary by the product and/or the time of day. It will be appreciated thatthe indicative opening price determined when the market is taken out ofthe reserved state, or a sampled, derived or measured value thereof, maybe used as the initial comparative value(s) by transaction integritymodules as described above upon resumption of trading.

Because market participants may not be aware that a product or aninstrument is reserved due to the large volume of messages sent over anelectronic trading system or because the market participants are nolonger trading, the present system and method also may encompassindependent communication systems to convey information, warnings, oralerts about an instrument in a reserved state. Such systems can includedevices that send and/or receive messages via telecommunication orwireless links such as portable phones, personal digital assistants(“PDAs”), and/or electronic mail devices, devices that send and/orreceive images and can print them on a tangible media such as faxes,etc. Preferably, these systems make market participants aware of thestate of the market in a narrow timeframe. It will be appreciated thatthe length of time for which the market may be temporarily held in areserved state is implementation dependent and may be configurable,statically or dynamically, and further may vary from market to market.Once the market is reopened, or otherwise taken out of reserved state,transaction integrity modules may be re-enabled to continue monitoringthe market as described herein.

It will be appreciated that some systems designed to detect and respondto extreme market changes may respond by merely setting a hard pricelimit, i.e. minimum or maximum depending upon the direction of theextreme movement, only within which trades are allowed to occur.However, setting either a maximum or minimum price limit and continuingto allow trading may not address the underlying problem which caused theextreme market movement and the market may reverse and undergo anextreme movement away from the set limit, such as due to the reaction ofalgorithmic trading systems. In contrast, transaction integrity modulesmay place the market in a reserved state whereby trades are not allowedbut price discovery can still occur. This effectively slows down themarket and enables traders to analyze the market and temper theirreactions thereto.

In one embodiment, the action may include placement of the market forthe product in a reserved state, as was described above, such as for alimited time period which may be configurable and may be a static ordynamic value and may vary among markets. In one embodiment, if duringthe reserved state additional conditions, such as based on whether themarket is recovering to a normal operating state or not as the reservedstate is nearing an end, are met, the time limit for staying in reservedstate may be extended. Alternatively, or in addition thereto, the actionmay include transmission of an alert to an operator of the exchange,such as the GCC of the CME, a trader of the product, or a combinationthereof. Alerts may be sent as market data. Where the market is placedin a reserved state, the alert may further advise the recipient of thisstate. A subsequent message may then be sent when the market is takenout of the reserved state or if the reserved state is extended.Alternatively, or in addition thereto, the action may include permanentor temporary enablement of trading opportunities for the product in adifferent market. For example, implied markets for which the currentproduct may be a leg, etc. may be enabled to create additional matchingopportunities, i.e. additional liquidity. Alternatively, or in additionthereto, the action may include permanent or temporary prevention oftrading of the product at a price outside of a price limit, i.e. aceiling or floor. If the detected extreme movement is downward, thelimit may set as a limit below which trading is not allowed, e.g. afloor. Alternatively, if the detected extreme movement of the market isupward, the limit may be set as a limit above which trading is notallowed, e.g. a ceiling. In one embodiment, if orders to trade aresubsequently received substantially close to, or at, or otherwise withina threshold of, the limit, the limit may be periodically raised (orlowered), such as after a defined delay period, to gradually allow amarket, intent on reaching a particular price, to eventually reach theprice in a controlled manner, e.g. the market is slowed down.

Upon reserving the market for a product, transaction integrity modulesmay release the market (i.e., resume allowing matching) as described inU.S. Pat. No. 8,924,278 entitled “System and method for controllingmarkets during a stop loss trigger”, the entire disclosure of which isincorporated by reference herein and relied upon. Alternatively,transaction integrity modules may release the market (i.e., resumeallowing matching) as described in the '936 Patent.

The illustrations of the embodiments described herein are intended toprovide a general understanding of the structure of the variousembodiments. The illustrations are not intended to serve as a completedescription of all of the elements and features of apparatus and systemsthat utilize the structures or methods described herein. Many otherembodiments may be apparent to those of skill in the art upon reviewingthe disclosure. Other embodiments may be utilized and derived from thedisclosure, such that structural and logical substitutions and changesmay be made without departing from the scope of the disclosure.Additionally, the illustrations are merely representational and may notbe drawn to scale. Certain proportions within the illustrations may beexaggerated, while other proportions may be minimized. Accordingly, thedisclosure and the figures are to be regarded as illustrative ratherthan restrictive.

While this specification contains many specifics, these should not beconstrued as limitations on the scope of the invention or of what may beclaimed, but rather as descriptions of features specific to particularembodiments of the invention. Certain features that are described inthis specification in the context of separate embodiments can also beimplemented in combination in a single embodiment. Conversely, variousfeatures that are described in the context of a single embodiment canalso be implemented in multiple embodiments separately or in anysuitable sub-combination. Moreover, although features may be describedas acting in certain combinations and even initially claimed as such,one or more features from a claimed combination can in some cases beexcised from the combination, and the claimed combination may bedirected to a sub-combination or variation of a sub-combination.

Similarly, while operations are depicted in the drawings and describedherein in a particular order, this should not be understood as requiringthat such operations be performed in the particular order shown or insequential order, or that all illustrated operations be performed, toachieve desirable results. In certain circumstances, multitasking andparallel processing may be advantageous. Moreover, the separation ofvarious system components in the described embodiments should not beunderstood as requiring such separation in all embodiments, and itshould be understood that the described program components and systemscan generally be integrated together in a single software product orpackaged into multiple software products.

One or more embodiments of the disclosure may be referred to herein,individually and/or collectively, by the term “invention” merely forconvenience and without intending to voluntarily limit the scope of thisapplication to any particular invention or inventive concept. Moreover,although specific embodiments have been illustrated and describedherein, it should be appreciated that any subsequent arrangementdesigned to achieve the same or similar purpose may be substituted forthe specific embodiments shown. This disclosure is intended to cover anyand all subsequent adaptations or variations of various embodiments.Combinations of the above embodiments, and other embodiments notspecifically described herein, will be apparent to those of skill in theart upon reviewing the description.

The Abstract of the Disclosure is provided to comply with 37 C.F.R. §1.72(b) and is submitted with the understanding that it will not be usedto interpret or limit the scope or meaning of the claims. In addition,in the foregoing Detailed Description, various features may be groupedtogether or described in a single embodiment for the purpose ofstreamlining the disclosure. This disclosure is not to be interpreted asreflecting an intention that the claimed embodiments require morefeatures than are expressly recited in each claim. Rather, as thefollowing claims reflect, inventive subject matter may be directed toless than all of the features of any of the disclosed embodiments. Thus,the following claims are incorporated into the Detailed Description,with each claim standing on its own as defining separately claimedsubject matter.

It is therefore intended that the foregoing detailed description beregarded as illustrative rather than limiting, and that it be understoodthat it is the following claims, including all equivalents, that areintended to define the spirit and scope of this invention.

1. A computer implemented method for optimizing processing of electronicdata multiple transaction request messages, the method comprising:receiving, by an optimization processor, an electronic data multipletransaction request message including a plurality of electronic datatransaction requests, each of the electronic data transaction requestsrequesting performance of a same type of transaction for a quantity ofthe same data object at a value, the electronic data transactionrequests sorted by value for each transaction type from the electronicdata transaction request associated with the best value to theelectronic data transaction request associated with the worst value;determining, by the optimization processor, whether the electronic datatransaction request associated with the best value will be rejected by atransaction integrity module of the data transaction processing system;and upon determining that the electronic data transaction requestassociated with the best value will be rejected by the transactionintegrity module, rejecting, by the optimization processor, theplurality of electronic data transaction requests.
 2. The computerimplemented method of claim 1, wherein the optimization processorrejects the electronic data transaction requests other than theelectronic data transaction request associated with the best valuewithout determining whether any of the electronic data transactionrequests other than the electronic data transaction request associatedwith the best value will be rejected by the transaction integritymodule.
 3. The computer implemented method of claim 1, whereindetermining, by the optimization processor, whether the electronic datatransaction request associated with the best value will be rejected bythe transaction integrity module comprises comparing the electronic datatransaction request associated with the best value to a bandingthreshold defining an allowable value range.
 4. The computer implementedmethod of claim 1, wherein determining, by the optimization processor,whether the electronic data transaction request associated with the bestvalue will be rejected by the transaction integrity module comprisesdetermining whether the best value fails velocity logic processing. 5.The computer implemented method of claim 1, further comprising:determining, by the optimization processor, whether an attempt to matchthe electronic data transaction request associated with the best valuewith at least one previously received but unsatisfied electronic datatransaction request for a transaction which is counter thereto resultsin at least partial satisfaction of one or both of the electronic datatransaction request associated with the best value and the at least onepreviously received but unsatisfied electronic data transaction request;and upon determining, by the optimization processor, that the attempt tomatch the electronic data transaction request associated with the bestvalue with at least one previously received but unsatisfied electronicdata transaction request for a transaction which is counter thereto willnot result in at least partial satisfaction of one or both of theelectronic data transaction request associated with the best value andthe at least one previously received but unsatisfied electronic datatransaction request, storing, by the optimization processor, dataassociated with the plurality of electronic data transaction requests inan order book object associated with the data object.
 6. The computerimplemented method of claim 5, wherein the optimization processor storesthe data associated with the electronic data transaction requests otherthan the electronic data transaction request associated with the bestvalue in the order book object associated with the data object withoutdetermining whether an attempt to match any of the electronic datatransaction requests other than the electronic data transaction requestassociated with the best value with at least one previously received butunsatisfied electronic data transaction request for a transaction whichis counter thereto results in at least partial satisfaction of one orboth of any of the electronic data transaction requests other than theelectronic data transaction request associated with the best value andthe at least one previously received but unsatisfied electronic datatransaction request.
 7. The computer implemented method of claim 1,wherein if the type of transaction is to relinquish the data object, theelectronic data transaction request associated with the best value isthe electronic data transaction request associated with the smallestvalue, and the electronic data transaction request associated with theworst value is the electronic data transaction request associated withthe largest value.
 8. The computer implemented method of claim 1,wherein if the type of transaction is to acquire the data object, theelectronic data transaction request associated with the best value isthe electronic data transaction request associated with the largestvalue, and the electronic data transaction request associated with theworst value is the electronic data transaction request associated withthe smallest value.
 9. The computer implemented method of claim 1,wherein the plurality of electronic data transaction requests is a firstplurality of electronic data transaction requests, wherein the type oftransaction for each of the first plurality of electronic datatransaction requests is to acquire the data object, and wherein theelectronic data multiple transaction request message includes a secondplurality of electronic data transaction requests, each of the secondplurality of electronic data transaction requests requestingrelinquishing a quantity of the data object at a value, the methodfurther comprising: determining whether all of the values associatedwith the first plurality of electronic data transaction requests areless than all of the values associated with the second plurality ofelectronic data transaction requests, and determining whether theelectronic data transaction request associated with the best value foracquiring the data object is greater than a lead acquisition valuestored in an order book object for the data object; and upon determiningthat all of the values associated with the first plurality of electronicdata transaction requests are less than all of the values associatedwith the second plurality of electronic data transaction requests, andthat the electronic data transaction request associated with the bestvalue for acquiring the data object is greater than the lead acquisitionvalue, storing, by the optimization processor, data associated with thesecond plurality of electronic data transaction requests in the orderbook object associated with the data object.
 10. The computerimplemented method of claim 9, wherein the optimization processor storesthe data associated with the second plurality of electronic datatransaction requests in the order book object associated with the dataobject without determining whether an attempt to match any of the secondplurality of electronic data transaction requests with at least onepreviously received but unsatisfied electronic data transaction requestto acquire the data object results in at least partial satisfaction ofone or both of any of the second plurality of electronic datatransaction requests and the at least one previously received butunsatisfied electronic data transaction request.
 11. The computerimplemented method of claim 10, wherein the lead acquisition value isthe best value from a plurality of previously received but unsatisfiedelectronic data transaction requests to acquire the data object.
 12. Thecomputer implemented method of claim 1, wherein upon determining thatthe electronic data multiple transaction request message includes anatomic instruction, the optimization processor determines whether, foreach of the plurality of the electronic data transaction requests, anattempt to match the electronic data transaction request with at leastone previously received but unsatisfied electronic data transactionrequest for a transaction which is counter thereto results in at leastpartial satisfaction of one or both of the electronic data transactionrequest and the at least one previously received but unsatisfiedelectronic data transaction request; and upon determining, by theoptimization processor, that, for each of the plurality of theelectronic data transaction requests, the attempt to match theelectronic data transaction request with at least one previouslyreceived but unsatisfied electronic data transaction request for atransaction which is counter thereto results in at least partialsatisfaction of one or both of the electronic data transaction requestand the at least one previously received but unsatisfied electronic datatransaction request, matching each of the plurality of the electronicdata transaction requests with the at least one previously received butunsatisfied electronic data transaction request.
 13. The computerimplemented method of claim 12, wherein the optimization processormatches each of the plurality of the electronic data transactionrequests with the at least one previously received but unsatisfiedelectronic data transaction request before attempting to match any otherelectronic data transaction request not in the electronic data multipletransaction request message.
 14. The computer implemented method ofclaim 1, wherein the data object is a first data object and theplurality of electronic data transaction requests is a first pluralityof electronic data transaction requests, and wherein the electronic datamultiple transaction request message includes a third plurality ofelectronic data transaction requests associated with a second dataobject.
 15. A computer system for optimizing processing of electronicdata multiple transaction request messages, the computer systemcomprising: an optimization processor configured to cause the computersystem to: receive an electronic data multiple transaction requestmessage including a plurality of electronic data transaction requests,each of the electronic data transaction requests requesting performanceof a same type of transaction for a quantity of the same data object ata value, the electronic data transaction requests sorted by value foreach transaction type from the electronic data transaction requestassociated with the best value to the electronic data transactionrequest associated with the worst value; determine whether theelectronic data transaction request associated with the best value willbe rejected by a transaction integrity module of the data transactionprocessing system; and upon determining that the electronic datatransaction request associated with the best value will be rejected bythe transaction integrity module, reject the plurality of electronicdata transaction requests.
 16. The computer system of claim 15, whereinthe optimization processor is further configured to cause the computersystem to: determine whether an attempt to match the electronic datatransaction request associated with the best value with at least onepreviously received but unsatisfied electronic data transaction requestfor a transaction which is counter thereto results in at least partialsatisfaction of one or both of the electronic data transaction requestassociated with the best value and the at least one previously receivedbut unsatisfied electronic data transaction request; and upondetermining that the attempt to match the electronic data transactionrequest associated with the best value with at least one previouslyreceived but unsatisfied electronic data transaction request for atransaction which is counter thereto will not result in at least partialsatisfaction of one or both of the electronic data transaction requestassociated with the best value and the at least one previously receivedbut unsatisfied electronic data transaction request, store dataassociated with the plurality of electronic data transaction requests inan order book object associated with the data object.
 17. The computersystem of claim 15, wherein if the type of transaction is to relinquishthe data object, the electronic data transaction request associated withthe best value is the electronic data transaction request associatedwith the smallest value, and the electronic data transaction requestassociated with the worst value is the electronic data transactionrequest associated with the largest value.
 18. The computer system ofclaim 15, wherein if the type of transaction is to acquire the dataobject, the electronic data transaction request associated with the bestvalue is the electronic data transaction request associated with thelargest value, and the electronic data transaction request associatedwith the worst value is the electronic data transaction requestassociated with the smallest value.
 19. The computer system of claim 15,wherein the plurality of electronic data transaction requests is a firstplurality of electronic data transaction requests, wherein the type oftransaction for each of the first plurality of electronic datatransaction requests is to acquire the data object, wherein theelectronic data multiple transaction request message includes a secondplurality of electronic data transaction requests, each of the secondplurality of electronic data transaction requests requestingrelinquishing a quantity of the data object at a value, and wherein theoptimization processor is further configured to cause the computersystem to: determine whether all of the values associated with the firstplurality of electronic data transaction requests are less than all ofthe values associated with the second plurality of electronic datatransaction requests, and determine whether the electronic datatransaction request associated with the best value for acquiring thedata object is greater than a lead acquisition value stored in an orderbook object for the data object; and upon determining that all of thevalues associated with the first plurality of electronic datatransaction requests are less than all of the values associated with thesecond plurality of electronic data transaction requests, and that theelectronic data transaction request associated with the best value foracquiring the data object is greater than the lead acquisition value,store data associated with the second plurality of electronic datatransaction requests in the order book object associated with the dataobject.
 20. A computer system comprising: means for receiving anelectronic data multiple transaction request message including aplurality of electronic data transaction requests, each of theelectronic data transaction requests requesting performance of a sametype of transaction for a quantity of the same data object at a value,the electronic data transaction requests sorted by value for eachtransaction type from the electronic data transaction request associatedwith the best value to the electronic data transaction requestassociated with the worst value; means for determining whether theelectronic data transaction request associated with the best value willbe rejected by a transaction integrity module of the data transactionprocessing system; and upon determining that the electronic datatransaction request associated with the best value will be rejected bythe transaction integrity module, means for rejecting the plurality ofelectronic data transaction requests.